# DeepInfra vs Baseten

Canonical: https://inetgeek.com/compare/deepinfra-vs-baseten/

Every value below is read from DeepInfra's and Baseten's own documentation. See https://inetgeek.com/methodology/ for how.

## At a glance

| Criterion | DeepInfra | Baseten |
| --- | --- | --- |
| Pricing model | Two products on one bill: per-token serverless inference with a separate cached-input rate for each model, and dedicated GPUs billed per minute and invoiced weekly. Models without per-token pricing are billed for inference execution time instead. | 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. |
| Input price, top model | $1.30 per million input tokens for DeepSeek-V4-Pro, the most expensive model in its catalogue. Cached input is $0.10. | $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. |
| Output price, top model | $2.60 per million output tokens for DeepSeek-V4-Pro. | $4.40 per million output tokens for GLM-5.3. |
| Input price, cheapest model | $0.06 per million input tokens for DeepSeek-V4-Flash-0731, with cached input at $0.015 and output at $0.18. DeepSeek itself charges $0.44 at peak for the same checkpoint and Fireworks $0.22. | $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. |
| Context window | 1024k tokens on the DeepSeek V4 models it serves; 160k on the V3 generation. The window is the model's rather than a platform limit. | 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. |
| Prompt caching | Supported | Supported |
| H100 SXM, per GPU-hour | $2.20 per GPU-hour for a dedicated H100 80GB — below every dedicated cloud in this dataset. A100 80GB is $0.89, H200 $2.69, B200 $3.69. Billed in minute granularity, invoiced weekly. | $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. |
| Largest GPU offered | 270GB per GPU on a B300, at $4.89 per GPU-hour. | 180GB per GPU on a B200, at $0.16633 per minute — $9.98 an hour. |

## Where they differ

### Pricing model

- DeepInfra: Two products on one bill: per-token serverless inference with a separate cached-input rate for each model, and dedicated GPUs billed per minute and invoiced weekly. Models without per-token pricing are billed for inference execution time instead. ([source](https://deepinfra.com/pricing))
- 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. ([source](https://www.baseten.co/pricing/))

### Input price, top model

- DeepInfra: $1.30 per million input tokens for DeepSeek-V4-Pro, the most expensive model in its catalogue. Cached input is $0.10. ([source](https://deepinfra.com/pricing))
- 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. ([source](https://www.baseten.co/pricing/))

### Output price, top model

- DeepInfra: $2.60 per million output tokens for DeepSeek-V4-Pro. ([source](https://deepinfra.com/pricing))
- Baseten: $4.40 per million output tokens for GLM-5.3. ([source](https://www.baseten.co/pricing/))

### Input price, cheapest model

- DeepInfra: $0.06 per million input tokens for DeepSeek-V4-Flash-0731, with cached input at $0.015 and output at $0.18. DeepSeek itself charges $0.44 at peak for the same checkpoint and Fireworks $0.22. ([source](https://deepinfra.com/pricing))
- 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. ([source](https://www.baseten.co/pricing/))

### Context window

- DeepInfra: 1024k tokens on the DeepSeek V4 models it serves; 160k on the V3 generation. The window is the model's rather than a platform limit. ([source](https://deepinfra.com/pricing))
- Baseten: 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. ([source](https://docs.baseten.co/inference/model-apis/overview))

### H100 SXM, per GPU-hour

- DeepInfra: $2.20 per GPU-hour for a dedicated H100 80GB — below every dedicated cloud in this dataset. A100 80GB is $0.89, H200 $2.69, B200 $3.69. Billed in minute granularity, invoiced weekly. ([source](https://deepinfra.com/pricing))
- 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. ([source](https://www.baseten.co/pricing/))

### Largest GPU offered

- DeepInfra: 270GB per GPU on a B300, at $4.89 per GPU-hour. ([source](https://deepinfra.com/pricing))
- Baseten: 180GB per GPU on a B200, at $0.16633 per minute — $9.98 an hour. ([source](https://www.baseten.co/pricing/))

## Which should you choose?

Pick DeepInfra if Running open-weight models at the lowest published per-token rates here — DeepSeek-V4-Flash at $0.06 per million input is a fraction of what the lab itself charges — with dedicated H100s at $2.20 an hour if throughput demands it.

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.

Consider something else: DeepInfra — Only some models carry per-token pricing; the rest bill for inference execution time, which is a different and harder thing to forecast.

Consider something else: 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.

## Documented by only one

- Entry paid plan: Baseten: $0 per month on the Basic plan — pay as you go, with dedicated deployments, model APIs and training included rather than gated behind a fee.
- 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.
- 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.

## Questions this comparison answers

**Should I choose DeepInfra or Baseten?**

Pick DeepInfra if Running open-weight models at the lowest published per-token rates here — DeepSeek-V4-Flash at $0.06 per million input is a fraction of what the lab itself charges — with dedicated H100s at $2.20 an hour if throughput demands it.
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.