Baseten vs Fireworks AI
SEPT 2026 auditA comparison of Baseten and Fireworks AI built from values read directly from each provider's own documentation, with the source recorded against every figure.
The short answer
Choose Baseten if…
Teams that want per-token APIs and dedicated GPUs from one vendor with no plan fee — minute-granularity billing means a model that runs for ten minutes costs ten minutes.
Editorial · Palash Bagchi · approved
Choose Fireworks AI if…
Running open-weight models without operating GPUs — the same DeepSeek and Qwen checkpoints the labs publish, served per token, with a path to dedicated hardware if throughput demands it.
Editorial · Palash Bagchi · approved
Consider something else if…
- Baseten: Its dedicated H100 works out at $6.50 an hour, roughly three times DeepInfra's, so steady GPU workloads pay a premium for the platform around them.
- Fireworks AI: You want a frontier proprietary model: Fireworks serves other people's open weights, so the ceiling is whatever the open ecosystem has released.
20 sourced criteria separate them — see where, with sources, below.
Pick the criteria you care about. The chart counts how many of them lean toward each provider — the same read as scanning the bars below, just totalled for the ones you chose.
Baseten 0
Fireworks AI 0
At a glance.
| Criterion | Baseten | Fireworks AI |
|---|---|---|
| Pricing | ||
| Free tier | No — New workspaces get starting credits for testing; usage beyond them is billed per minute. | No |
| Kind of free offer | Free credit | Free credit |
| Pricing model | No platform fee: per-token Model APIs for open models, and dedicated deployments billed per minute of compute with volume discounts. The Pro tier buys priority access to high-demand GPUs rather than a lower rate. | Three products on one bill. Serverless inference is per token, per model. Fine-tuning is per million TRAINING tokens by parameter band — $0.50 for models up to 16B, $10.00 above 300B. Dedicated GPUs are hourly: $7.00 for an H100 or H200, $10.00 for a B200. |
| Infrastructure | ||
| Regions | Two Baseten regions selectable for regional deployments: us (United States) and eu (European Union); other regions by request to support. GPU model deployments only; Chains, training jobs and shared CPU types cannot select a region. | Multi-regions GLOBAL, US, EUROPE and APAC, plus 26 named Fireworks-managed single regions (US, Canada, Frankfurt, Iceland, Tokyo, New South Wales, Malaysia) for dedicated deployments. Only GLOBAL has quota by default; other placements must be granted by Fireworks. |
| Inference | ||
| Input price, top model | $1.40 per million input tokens for GLM-5.3, with cached input at $0.14 and output at $4.40. GLM-5.2 Fast, a speed variant, is $2.10. | $3.00 per million input tokens for Kimi K3, the most expensive model in its serverless catalogue. Fireworks hosts other labs' open-weight models rather than its own, so "flagship" here means the top of what it serves. |
| Output price, top model | $4.40 per million output tokens for GLM-5.3. | $15.00 per million output tokens for Kimi K3. |
| Input price, cheapest model | $0.10 per million input tokens for GPT OSS 120B, with output at $0.50. GLM-5.3-Flash is $0.15 in and $0.50 out. | $0.15 per million input tokens for GLM 5.3 Flash, with output at $0.50. DeepSeek-V4-Flash is $0.22 in and $0.66 out — the same model DeepSeek itself sells at $0.44 peak. |
| Context window | 1,048K tokens on the DeepSeek V4 line and the GLM 5.2/5.3 family, the widest it serves; 262K on the Kimi K2 models, 200K on GLM 4.7 and 128K on GPT OSS 120B. Baseten's table publishes these in thousands, so the magnitude is 1,048,000 rather than the 1,048,576 a power-of-two reading would give — the vendor's own figure, not a conversion of it. | 1,048,576 tokens on Kimi K3, GLM 5.3 and both DeepSeek V4 variants; 262,144 on Qwen3.8 and 131,072 on Muse Glimmer 30B. The window is the model's, not Fireworks'. |
| Max output tokens | 262K tokens on most models, and it is a separate ceiling from the context window rather than the remainder of it: DeepSeek V4 Flash 0731 allows 384K output inside a 1,048K window, while GLM 4.7, Nemotron Ultra and GPT OSS 120B cap output at their full context. The Inkling models are the outlier at 32K. | No separate output cap. max_tokens is bounded by the model's context length — prompt plus completion must fit inside it — and what happens on overflow is set by context_length_exceeded_behavior rather than a fixed ceiling. |
| Prompt caching | Supported | Supported |
| Rate limits | Two limits, requests and tokens per minute, set by account status rather than spend: an unverified Basic account gets 15 RPM and 100,000 TPM, a verified Basic or Pro account 120 RPM and 500,000 TPM, Enterprise custom. Cached input counts toward TPM at full weight even though it is billed cheaper. | Adaptive serverless TPM ceilings by model size: 64.8M total prompt / 648k generated TPM under 400B params, down to 21.6M / 216k at 1.6T+ params. Ceilings are upper bounds; effective limits ramp with usage and spending tier. |
| GPU | ||
| H100 SXM, per GPU-hour | $6.50 per hour for a dedicated H100 80GB. Baseten publishes $0.10833 per MINUTE — the hourly figure is that times 60, ours rather than Baseten's, and the page offers an hourly toggle. A100 80GB is $0.06667 a minute and B200 $0.16633. | $7.00 per hour for an H100 80GB on demand, or $8.00 on the shorter commitment shown beside it. The same rate applies to an H200 141GB. |
| Largest GPU offered | 180GB per GPU on a B200, at $0.16633 per minute — $9.98 an hour. | 180GB per GPU on a B200, at $10.00 an hour on demand. |
| Compliance | ||
| SOC 2 | Maintains SOC 2 Type II certification for the inference platform; policies and certifications are held in the Baseten Trust Center. | SOC 2 Type II certified; audit reports available in the Fireworks Trust Center. |
| ISO 27001 | ISO 27001:2022 listed as a compliance program; an ISO 27001 certificate for Baseten Labs, Inc. is published in the Trust Center for request. Certificate is request-access in the Trust Center, not a public download. | ISO 27001 achieved for its ISMS, alongside ISO 27701 and ISO 42001; certificate PDFs downloadable from the Fireworks Trust Center. |
| HIPAA | Maintains HIPAA compliance alongside SOC 2 Type II for model inference on the Baseten platform. | States it is HIPAA compliant and supports healthcare and life sciences organizations. |
| GDPR / data residency | Baseten Cloud supports a GDPR compliance program; residency is set with regional environments or a region on a single deployment. | Enterprise-only data residency pins all account inference to one region; US (us.api.fireworks.ai) is the only listed option, default is None, other regions via sales. |
| PCI DSS | PCI DSS - SAQ D listed as a compliance program; a PCI-DSS v4.0.1 AOC for SAQ D Service Provider is published in the Trust Center for request. SAQ D self-assessment AOC, not a QSA Report on Compliance. | Data Processing Addendum states Fireworks is not PCI compliant and has no obligation to become so; payment card data is Prohibited Personal Data. |
| Encryption at rest | Trust Center control: datastores housing sensitive customer data are encrypted at rest, and transmission over public networks is encrypted. | Encrypted at rest with AES-256, and in transit with TLS 1.2+. |
| Customer-managed keys | Runtime OIDC BYOK recipes: a model fetches customer-managed keys at runtime to decrypt encrypted weights and to decrypt requests and encrypt responses. Documented under runtime OIDC use cases, implemented in model code via the truss-examples envelope-encryption recipes. | Bring your own AWS KMS, Google Cloud KMS or Azure Key Vault key; CMEK covers training datasets and checkpoints (LoRA SFT, DPO, RFT), not full-parameter training. Final model weights listed as "Coming soon" on the same page. |
| Role-based access control | Role-based access control with three organization roles - Admin, Member and Viewer - in a single-team organization. | Four account roles - Admin, User, Contributor and Inference User - with documented per-role resource and API-key permissions. Contributor and Inference User must be enabled by Fireworks support. |
| Private networking / VPC | Single-tenant Enterprise environments expose endpoints via AWS PrivateLink or Google Cloud Private Service Connect, off the public internet. | Bring Your Own Cluster (Enterprise, Private Preview) runs Fireworks inference inside your own Kubernetes cluster, cloud account or data-center network boundary. |
| Dedicated infrastructure | Single-tenant runs workloads in an isolated VPC in Baseten Cloud with compute restricted to your organization; Enterprise, custom pricing. | On-demand deployments run on dedicated GPUs billed per GPU-second, with no hard rate limits and performance unaffected by other users. |
Where they differ.
Pricing model
- Baseten
- No platform fee: per-token Model APIs for open models, and dedicated deployments billed per minute of compute with volume discounts. The Pro tier buys priority access to high-demand GPUs rather than a lower rate.
- Fireworks AI
- Three products on one bill. Serverless inference is per token, per model. Fine-tuning is per million TRAINING tokens by parameter band — $0.50 for models up to 16B, $10.00 above 300B. Dedicated GPUs are hourly: $7.00 for an H100 or H200, $10.00 for a B200.
Sources (2) →Sources ↓
- Pricing — Baseten ↗
“$0 per month, pay as you go [...] Only pay for the compute you use, down to the minute. Volume discounts available [...] Pro Unlimited autoscaling and priority compute access [...] Priority access to high-demand GPUs”
Read 2026-09-06 · official pricing · Report a correction
- Pricing — Fireworks AI ↗
“MODELS UP TO 16B PARAMETERS $0.50 $1.00 $1.00 $2.00 [...] MODELS >300B (E.G. DEEPSEEK V3, KIMI K2) $10.00 $20.00 $20.00 $40.00 [...] H100 80 GB GPU $7.00 $8.00 H200 141 GB GPU $7.00 $8.00 B200 180 GB GPU $10.00 $13.00”
Read 2026-09-06 · official pricing · Report a correction
Regions
- Baseten
- Two Baseten regions selectable for regional deployments: us (United States) and eu (European Union); other regions by request to support. GPU model deployments only; Chains, training jobs and shared CPU types cannot select a region.
- Fireworks AI
- Multi-regions GLOBAL, US, EUROPE and APAC, plus 26 named Fireworks-managed single regions (US, Canada, Frankfurt, Iceland, Tokyo, New South Wales, Malaysia) for dedicated deployments. Only GLOBAL has quota by default; other placements must be granted by Fireworks.
Sources (2) →Sources ↓
- Regional deployments - Baseten ↗
“The following regions are available for regional deployments. [...] us United States eu European Union”
Read 2026-09-13 · official docs · Report a correction
- Regions - Fireworks AI Docs ↗
“Supported multi-regions: GLOBAL , US , EUROPE , APAC . [...] Single regions are concrete locations (e.g. US_IOWA_1 , EU_FRANKFURT_1 ) where your deployment can run.”
Read 2026-09-13 · official docs · Report a correction
Input price, top model
- Baseten
- $1.40 per million input tokens for GLM-5.3, with cached input at $0.14 and output at $4.40. GLM-5.2 Fast, a speed variant, is $2.10.
- Fireworks AI
- $3.00 per million input tokens for Kimi K3, the most expensive model in its serverless catalogue. Fireworks hosts other labs' open-weight models rather than its own, so "flagship" here means the top of what it serves.
Sources (2) →Sources ↓
- Pricing — Baseten ↗
“GLM-5.3 GLM-5.3 $1.40 $1.40 $0.14 $0.14 $4.40 [...] GLM-5.2 Fast GLM-5.2 Fast $2.10 $2.10 $0.21”
Read 2026-09-06 · official pricing · Report a correction
- Models — Fireworks AI ↗
“Kimi K3 $3/M Input • $15/M Output • 1048576 Context”
Read 2026-09-06 · official pricing · Report a correction
Output price, top model
- Baseten
- $4.40 per million output tokens for GLM-5.3.
- Fireworks AI
- $15.00 per million output tokens for Kimi K3.
Sources (2) →Sources ↓
- Pricing — Baseten ↗
“GLM-5.3 GLM-5.3 $1.40 $1.40 $0.14 $0.14 $4.40”
Read 2026-09-06 · official pricing · Report a correction
- Models — Fireworks AI ↗
“Kimi K3 $3/M Input • $15/M Output • 1048576 Context”
Read 2026-09-06 · official pricing · Report a correction
Input price, cheapest model
- Baseten
- $0.10 per million input tokens for GPT OSS 120B, with output at $0.50. GLM-5.3-Flash is $0.15 in and $0.50 out.
- Fireworks AI
- $0.15 per million input tokens for GLM 5.3 Flash, with output at $0.50. DeepSeek-V4-Flash is $0.22 in and $0.66 out — the same model DeepSeek itself sells at $0.44 peak.
Sources (2) →Sources ↓
- Pricing — Baseten ↗
“GPT OSS 120B GPT OSS 120B $0.10 $0.10 - - $0.50 [...] GLM-5.3-Flash GLM-5.3-Flash $0.15 $0.15 $0.03 $0.03 $0.50”
Read 2026-09-06 · official pricing · Report a correction
- Models — Fireworks AI ↗
“GLM 5.3 Flash $0.15/M Input • $0.5/M Output • 1048576 Context [...] DeepSeek-V4-Flash-0731 $0.22/M Input • $0.66/M Output • 1048576 Context”
Read 2026-09-06 · official pricing · Report a correction
Context window
1,048K tokens on the DeepSeek V4 line and the GLM 5.2/5.3 family, the widest it serves; 262K on the Kimi K2 models, 200K on GLM 4.7 and 128K on GPT OSS 120B. Baseten's table publishes these in thousands, so the magnitude is 1,048,000 rather than the 1,048,576 a power-of-two reading would give — the vendor's own figure, not a conversion of it.
1,048,576 tokens on Kimi K3, GLM 5.3 and both DeepSeek V4 variants; 262,144 on Qwen3.8 and 131,072 on Muse Glimmer 30B. The window is the model's, not Fireworks'.
Sources (2) →Sources ↓
- Model APIs overview — Baseten Docs ↗
“SupportedModelsTable [...] model: "DeepSeek V4 Pro", context: 1048, maxOutput: 262 [...] model: "GLM 5.3", context: 1048, maxOutput: 262 [...] model: "GLM 4.7", context: 200, maxOutput: 200 [...] model: "OpenAI GPT 120B", context: 128, maxOutput: 128”
Read 2026-09-08 · official docs · Report a correction
- Models — Fireworks AI ↗
“Kimi K3 $3/M Input • $15/M Output • 1048576 Context [...] Qwen3.8-2.4T-A95B $2/M Input • $6/M Output • 262144 Context [...] Muse Glimmer 30B $0.35/M Input • $1.5/M Output • 131072 Context”
Read 2026-09-06 · official pricing · Report a correction
Max output tokens
- Baseten
- 262K tokens on most models, and it is a separate ceiling from the context window rather than the remainder of it: DeepSeek V4 Flash 0731 allows 384K output inside a 1,048K window, while GLM 4.7, Nemotron Ultra and GPT OSS 120B cap output at their full context. The Inkling models are the outlier at 32K.
- Fireworks AI
- No separate output cap. max_tokens is bounded by the model's context length — prompt plus completion must fit inside it — and what happens on overflow is set by context_length_exceeded_behavior rather than a fixed ceiling.
Sources (2) →Sources ↓
- Model APIs overview — Baseten Docs ↗
“SupportedModelsTable [...] model: "DeepSeek V4 Pro", context: 1048, maxOutput: 262 [...] model: "GLM 5.3", context: 1048, maxOutput: 262 [...] model: "GLM 4.7", context: 200, maxOutput: 200 [...] model: "OpenAI GPT 120B", context: 128, maxOutput: 128”
Read 2026-09-08 · official docs · Report a correction
- Chat Completions API — Fireworks docs ↗
“The maximum number of tokens to generate in the completion. If the token count of your prompt plus max_tokens exceeds the model's context length, the behavior depends on context_length_exceeded_behavior.”
Read 2026-09-07 · official docs · Report a correction
Rate limits
- Baseten
- Two limits, requests and tokens per minute, set by account status rather than spend: an unverified Basic account gets 15 RPM and 100,000 TPM, a verified Basic or Pro account 120 RPM and 500,000 TPM, Enterprise custom. Cached input counts toward TPM at full weight even though it is billed cheaper.
- Fireworks AI
- Adaptive serverless TPM ceilings by model size: 64.8M total prompt / 648k generated TPM under 400B params, down to 21.6M / 216k at 1.6T+ params. Ceilings are upper bounds; effective limits ramp with usage and spending tier.
Sources (2) →Sources ↓
- Pricing and limits — Baseten Docs ↗
“Basic (unverified) | 15 | 100,000 | Basic (verified) | 120 | 500,000 | Pro | 120 | 500,000 [...] Cached and uncached input tokens count equally toward this limit, even though cached tokens cost less.”
Read 2026-09-07 · official docs · Report a correction
- Serverless Rate Limits - Fireworks AI Docs ↗
“Adaptive rate limit ceilings depend on the model’s total parameter count. Smaller models get higher ceilings: [...] 400B 64.8M 16.2M 648k [...] 1.6T 21.6M 5.4M 216k”
Read 2026-09-13 · official docs · Report a correction
H100 SXM, per GPU-hour
- Baseten
- $6.50 per hour for a dedicated H100 80GB. Baseten publishes $0.10833 per MINUTE — the hourly figure is that times 60, ours rather than Baseten's, and the page offers an hourly toggle. A100 80GB is $0.06667 a minute and B200 $0.16633.
- Fireworks AI
- $7.00 per hour for an H100 80GB on demand, or $8.00 on the shorter commitment shown beside it. The same rate applies to an H200 141GB.
Sources (2) →Sources ↓
- Pricing — Baseten ↗
“Dedicated Deployments Only pay for the compute you use, down to the minute. [...] Price per Minute Hour [...] A100 80 GiB VRAM $0.06667 [...] H100 80 GiB VRAM $0.10833 [...] B200 180 GiB VRAM $0.16633”
Read 2026-09-06 · official pricing · Report a correction
- Pricing — Fireworks AI ↗
“H100 80 GB GPU $7.00 $8.00 H200 141 GB GPU $7.00 $8.00 B200 180 GB GPU $10.00 $13.00”
Read 2026-09-06 · official pricing · Report a correction
Largest GPU offered
180GB per GPU on a B200, at $0.16633 per minute — $9.98 an hour.
180GB per GPU on a B200, at $10.00 an hour on demand.
Sources (2) →Sources ↓
- Pricing — Baseten ↗
“B200 180 GiB VRAM $0.16633 Deploy”
Read 2026-09-06 · official pricing · Report a correction
- Pricing — Fireworks AI ↗
“B200 180 GB GPU $10.00 $13.00”
Read 2026-09-06 · official pricing · Report a correction
SOC 2
- Baseten
- Maintains SOC 2 Type II certification for the inference platform; policies and certifications are held in the Baseten Trust Center.
- Fireworks AI
- SOC 2 Type II certified; audit reports available in the Fireworks Trust Center.
Sources (2) →Sources ↓
- Secure model inference - Baseten ↗
“Baseten maintains SOC 2 Type II certification and HIPAA compliance.”
Read 2026-09-13 · official docs · Report a correction
- Data Security - Fireworks AI Docs ↗
“SOC 2 Type II (certified) [...] Documentation and audit reports are available in our Trust Center”
Read 2026-09-13 · official docs · Report a correction
ISO 27001
- Baseten
- ISO 27001:2022 listed as a compliance program; an ISO 27001 certificate for Baseten Labs, Inc. is published in the Trust Center for request. Certificate is request-access in the Trust Center, not a public download.
- Fireworks AI
- ISO 27001 achieved for its ISMS, alongside ISO 27701 and ISO 42001; certificate PDFs downloadable from the Fireworks Trust Center.
Sources (2) →Sources ↓
- Baseten Trust Center ↗
“Compliance SOC 2 ISO 27001:2022 HIPAA [...] Baseten Labs, Inc. ISO 27001 Certificate.pdf”
Read 2026-09-13 · official site · Report a correction
- Data Security - Fireworks AI Docs ↗
“Fireworks has achieved all three ISO certifications covering security, privacy, and AI management: [...] Certificate PDFs for all three certifications are available for download from the Fireworks Trust Center”
Read 2026-09-13 · official docs · Report a correction
HIPAA
- Baseten
- Maintains HIPAA compliance alongside SOC 2 Type II for model inference on the Baseten platform.
- Fireworks AI
- States it is HIPAA compliant and supports healthcare and life sciences organizations.
Sources (2) →Sources ↓
- Secure model inference - Baseten ↗
“Baseten maintains SOC 2 Type II certification and HIPAA compliance.”
Read 2026-09-13 · official docs · Report a correction
- Data Security - Fireworks AI Docs ↗
“Fireworks is HIPAA compliant and supports healthcare and life sciences organizations in leveraging our rapid inference capabilities with confidence.”
Read 2026-09-13 · official docs · Report a correction
GDPR / data residency
- Baseten
- Baseten Cloud supports a GDPR compliance program; residency is set with regional environments or a region on a single deployment.
- Fireworks AI
- Enterprise-only data residency pins all account inference to one region; US (us.api.fireworks.ai) is the only listed option, default is None, other regions via sales.
Sources (2) →Sources ↓
- Baseten Cloud - Baseten ↗
“Baseten Cloud supports SOC 2 Type II, HIPAA, and GDPR compliance programs. [...] to constrain workloads and inference traffic to specific regions”
Read 2026-09-13 · official docs · Report a correction
- Data residency - Fireworks AI Docs ↗
“Data residency restricts inference on your account to a single region. Once a region is set, every request must use that region’s API endpoint and a model served in that region. [...] Data residency is available on Enterprise accounts. [...] None is the default. For a region that is not listed, contact sales”
Read 2026-09-13 · official docs · Report a correction
PCI DSS
- Baseten
- PCI DSS - SAQ D listed as a compliance program; a PCI-DSS v4.0.1 AOC for SAQ D Service Provider is published in the Trust Center for request. SAQ D self-assessment AOC, not a QSA Report on Compliance.
- Fireworks AI
- Data Processing Addendum states Fireworks is not PCI compliant and has no obligation to become so; payment card data is Prohibited Personal Data.
Sources (2) →Sources ↓
- Baseten Trust Center ↗
“GDPR PCI DSS - SAQ D [...] PCI-DSS-v4-0-1-AOC-for-SAQ-D-Service-Provider-r1.pdf”
Read 2026-09-13 · official site · Report a correction
- Fireworks AI Data Processing Addendum (PDF) ↗
“that Company is not PCI compliant, and is under no obligation to become PCI compliant [...] or (b) payment card data, including credit card or debit card numbers.”
Read 2026-09-13 · official docs · Report a correction
Encryption at rest
- Baseten
- Trust Center control: datastores housing sensitive customer data are encrypted at rest, and transmission over public networks is encrypted.
- Fireworks AI
- Encrypted at rest with AES-256, and in transit with TLS 1.2+.
Sources (2) →Sources ↓
- Baseten Trust Center - Controls ↗
“The company's datastores housing sensitive customer data are encrypted at rest. [...] The company uses secure data transmission protocols to encrypt confidential and sensitive data when transmitted over public networks.”
Read 2026-09-13 · official site · Report a correction
- Data Security - Fireworks AI Docs ↗
“Data is encrypted in transit (TLS 1.2+) and at rest (AES-256).”
Read 2026-09-13 · official docs · Report a correction
Customer-managed keys
- Baseten
- Runtime OIDC BYOK recipes: a model fetches customer-managed keys at runtime to decrypt encrypted weights and to decrypt requests and encrypt responses. Documented under runtime OIDC use cases, implemented in model code via the truss-examples envelope-encryption recipes.
- Fireworks AI
- Bring your own AWS KMS, Google Cloud KMS or Azure Key Vault key; CMEK covers training datasets and checkpoints (LoRA SFT, DPO, RFT), not full-parameter training. Final model weights listed as "Coming soon" on the same page.
Sources (2) →Sources ↓
- OpenID Connect (OIDC) authentication - Baseten ↗
“Keep model weights encrypted in object storage and use runtime OIDC to retrieve the key material needed to decrypt them when the model starts. [...] Use runtime OIDC to retrieve customer-managed keys, then decrypt requests and encrypt responses during inference.”
Read 2026-09-13 · official docs · Report a correction
- Data Security - Fireworks AI Docs ↗
“Customers may integrate their own AWS KMS, Google Cloud KMS, or Azure Key Vault key to retain governance and apply their own encryption policies. [...] Customer-Managed Encryption Keys for Training (LoRA SFT, DPO, and RFT; full-parameter training not supported)”
Read 2026-09-13 · official docs · Report a correction
Role-based access control
- Baseten
- Role-based access control with three organization roles - Admin, Member and Viewer - in a single-team organization.
- Fireworks AI
- Four account roles - Admin, User, Contributor and Inference User - with documented per-role resource and API-key permissions. Contributor and Inference User must be enabled by Fireworks support.
Sources (2) →Sources ↓
- Access control - Baseten ↗
“Baseten uses role-based access control (RBAC) to manage organization access. [...] In organizations that use a single team, every organization member has one of three roles.”
Read 2026-09-13 · official docs · Report a correction
- Managing users - Fireworks AI Docs ↗
“Each user in an account is assigned a role that determines their level of access: [...] The contributor and inference-user roles are newer roles that provide more granular access control.”
Read 2026-09-13 · official docs · Report a correction
Private networking / VPC
- Baseten
- Single-tenant Enterprise environments expose endpoints via AWS PrivateLink or Google Cloud Private Service Connect, off the public internet.
- Fireworks AI
- Bring Your Own Cluster (Enterprise, Private Preview) runs Fireworks inference inside your own Kubernetes cluster, cloud account or data-center network boundary.
Sources (2) →Sources ↓
- Single-tenant - Baseten ↗
“Inference requests route directly from your application to your dedicated environment and can remain off the public internet. [...] such as AWS PrivateLink or Google Cloud Private Service Connect”
Read 2026-09-13 · official docs · Report a correction
- Bring Your Own Cluster - Fireworks AI Docs ↗
“Bring Your Own Cluster (BYOC) lets Enterprise customers run Fireworks inference inside their own Kubernetes cluster. Your inference compute runs in your cloud account or data center boundary, while Fireworks installs and operates the serving stack for you. [...] Bring Your Own Cluster is in Private Preview for Enterprise customers.”
Read 2026-09-13 · official docs · Report a correction
Dedicated infrastructure
- Baseten
- Single-tenant runs workloads in an isolated VPC in Baseten Cloud with compute restricted to your organization; Enterprise, custom pricing.
- Fireworks AI
- On-demand deployments run on dedicated GPUs billed per GPU-second, with no hard rate limits and performance unaffected by other users.
Sources (2) →Sources ↓
- Single-tenant - Baseten ↗
“Single-tenant runs your inference workloads in an isolated VPC in Baseten Cloud. [...] Compute and scheduling are restricted to your organization. [...] Single-tenant is available with custom pricing on the Enterprise plan.”
Read 2026-09-13 · official docs · Report a correction
- Deployments - Fireworks AI Docs ↗
“On-demand deployments give you dedicated GPUs for your models, providing several advantages over serverless: [...] Lower latency, higher throughput, and predictable performance unaffected by other users [...] on-demand deployments are billed by GPU-second”
Read 2026-09-13 · official docs · Report a correction
When these numbers change, hear about it. Sources are re-checked monthly; a repricing goes out as a short note.
Documented by only one.
These criteria are published by one provider and not the other. An absence here means we have not found a source, not that the feature is missing — except where we say we read the other provider's own page on a given date and it does not state it. Those rows lean, and the provider can correct them with a link.
Questions this comparison answers.
Should I choose Baseten or Fireworks AI?
Pick Baseten if Teams that want per-token APIs and dedicated GPUs from one vendor with no plan fee — minute-granularity billing means a model that runs for ten minutes costs ten minutes.
Pick Fireworks AI if Running open-weight models without operating GPUs — the same DeepSeek and Qwen checkpoints the labs publish, served per token, with a path to dedicated hardware if throughput demands it.
Comments are hosted by EchoThread, which sets cookies and offers social sign-in. Like the analytics on this site, it does not load until you accept — see the privacy page.