# Fireworks AI vs Google Gemini API

Canonical: https://inetgeek.com/compare/fireworks-vs-google-gemini/

Every value below is read from Fireworks AI's and Google Gemini API's own documentation. See https://inetgeek.com/methodology/ for how.

## At a glance

| Criterion | Fireworks AI | Google Gemini API |
| --- | --- | --- |
| Free tier | Yes | Yes |
| Pricing model | 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. | Per million tokens, with dated price changes published in advance — the current Gemini 3.x rates are explicitly promotional through 31 December 2026 and roughly double on 1 January 2027. A free tier exists, and its content is used to improve Google's products where the paid tier's is not. |
| Input price, top model | $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. | $0.75 per million input tokens for Gemini 3.8 Flash through 31 December 2026, then $1.50. Gemini 3.1 Pro, still preview, is $2.00 for prompts up to 200k tokens and $4.00 above. |
| Output price, top model | $15.00 per million output tokens for Kimi K3. | $3.75 per million output tokens for Gemini 3.8 Flash through 31 December 2026, then $7.50. Thinking tokens are billed as output. |
| Input price, cheapest model | $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. | $0.30 per million input tokens for Gemini 3.5 Flash-Lite, with output at $2.50. |
| Context window | 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'. | 1,048,576 tokens for Gemini 3.8 Flash. Read from the Vertex AI model card: the Gemini API docs build their model cards client-side and publish no figure a fetch can read. |
| Max output tokens | 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. | 65,536 tokens for Gemini 3.8 Flash, and Google counts thinking tokens as output. |
| Prompt caching | Supported | Supported |

## Where they differ

### Pricing model

- 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. ([source](https://fireworks.ai/pricing))
- Google Gemini API: Per million tokens, with dated price changes published in advance — the current Gemini 3.x rates are explicitly promotional through 31 December 2026 and roughly double on 1 January 2027. A free tier exists, and its content is used to improve Google's products where the paid tier's is not. ([source](https://ai.google.dev/gemini-api/docs/pricing))

### Input price, top model

- 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. ([source](https://fireworks.ai/models))
- Google Gemini API: $0.75 per million input tokens for Gemini 3.8 Flash through 31 December 2026, then $1.50. Gemini 3.1 Pro, still preview, is $2.00 for prompts up to 200k tokens and $4.00 above. ([source](https://ai.google.dev/gemini-api/docs/pricing))

### Output price, top model

- Fireworks AI: $15.00 per million output tokens for Kimi K3. ([source](https://fireworks.ai/models))
- Google Gemini API: $3.75 per million output tokens for Gemini 3.8 Flash through 31 December 2026, then $7.50. Thinking tokens are billed as output. ([source](https://ai.google.dev/gemini-api/docs/pricing))

### Input price, cheapest model

- 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. ([source](https://fireworks.ai/models))
- Google Gemini API: $0.30 per million input tokens for Gemini 3.5 Flash-Lite, with output at $2.50. ([source](https://ai.google.dev/gemini-api/docs/pricing))

### Context window

- Fireworks AI: 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'. ([source](https://fireworks.ai/models))
- Google Gemini API: 1,048,576 tokens for Gemini 3.8 Flash. Read from the Vertex AI model card: the Gemini API docs build their model cards client-side and publish no figure a fetch can read. ([source](https://cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-8-flash))

### Max output tokens

- 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. ([source](https://fireworks.ai/docs/api-reference/post-chatcompletions))
- Google Gemini API: 65,536 tokens for Gemini 3.8 Flash, and Google counts thinking tokens as output. ([source](https://cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-8-flash))

## Which should you choose?

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.

Pick Google Gemini API if Getting to a working prototype without a card, then staying on the cheapest frontier-adjacent rates in this set — $0.75 per million input tokens is well under half what Anthropic and OpenAI charge for their top models.

Consider something else: 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.

Consider something else: Google Gemini API — The rates are dated: they roughly double on 1 January 2027, free-tier content is used to improve Google's products, and rate limits are not published anywhere you can read before signing up.

## Documented by only one

- Batch discount: Google Gemini API: 50% off through the Batch API, which is a paid-tier feature.
- Rate limits: Google Gemini API: Tied to a usage tier — Free, then Tier 1/2/3 unlocked by cumulative spend — and enforced as requests per minute, input tokens per minute and requests per day. Google publishes no numbers in the docs: limits are viewed in AI Studio and are stated not to be guaranteed.
- H100 SXM, per GPU-hour: 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.
- Largest GPU offered: Fireworks AI: 180GB per GPU on a B200, at $10.00 an hour on demand.

## Questions this comparison answers

**Should I choose Fireworks AI or Google Gemini API?**

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.
Pick Google Gemini API if Getting to a working prototype without a card, then staying on the cheapest frontier-adjacent rates in this set — $0.75 per million input tokens is well under half what Anthropic and OpenAI charge for their top models.