Gemma 3 7B: pricing, context window and benchmarks
Gemma 3 7B is a small open-weight model from Google DeepMind. It offers a 32,768-token context window, costs $0.90 per million input tokens and $4.55 per million output tokens, and averages 55.9 across the index's benchmark suite.
Pricing
Gemma 3 7B costs $0.90 per million input tokens and $4.55 per million output tokens. A blended 3:1 input-to-output mix works out to about $1.81 per million tokens. Cached input is listed at $0.12 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $0.90 | per 1M tokens |
| Output | $4.55 | per 1M tokens |
| Cached input | $0.12 | per 1M tokens |
| Blended 3:1 | $1.81 | estimate per 1M tokens |
| 1M in + 1M out | $5.45 | estimate |
Benchmarks
Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 60.8 | 514 | 14th | |
| GPQA Diamond | 54.0 | 482 | 20th | |
| SWE-bench Verified | 38.8 | 529 | 12th | |
| HumanEval | 61.2 | 482 | 20th | |
| MATH-500 | 56.2 | 505 | 16th | |
| AIME 2025 | 47.7 | 471 | 22th | |
| LiveCodeBench | 42.8 | 519 | 14th | |
| IFEval | 65.6 | 527 | 12th | |
| TruthfulQA | 59.3 | 538 | 10th | |
| HellaSwag | 72.2 | 491 | 18th | |
| MMMU | 56.8 | 474 | 21th | |
| Arena Elo | 1236.8 | 519 | 14th |
What Gemma 3 7B is good for
Gemma 3 7B is a small model. That makes it a good fit for classification, extraction, routing, summarization and other high-volume jobs where latency and cost dominate. It is not the right pick for open-ended frontier reasoning, but at $0.90 per million input tokens it can handle a large share of production traffic.
Strengths
- Input price of $0.90 per million tokens is at or below the index median.
- Open weights make self-hosting, fine-tuning and data-residency review possible.
Trade-offs
- Average benchmark score is below the index median; test it on your own task.
- Less reliable on open-ended reasoning and complex multi-step instructions.
How it compares
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Llama 3 Hyperbolic 8B | Hyperbolic | 16384 | $0.92 | 56.0 |
| Llama 3 Replicate 7B | Replicate | 32768 | $0.91 | 56.0 |
| Gemma 3 7B | Google DeepMind | 32768 | $0.90 | 55.9 |
| Pythia Base | EleutherAI | 16384 | $0.99 | 55.9 |
| Yi-Lightning 7B | 01.AI | 32768 | $1.00 | 55.9 |
| Embed 4 Mini | Cohere | 4096 | $2.48 | 55.8 |
FAQ
How much does Gemma 3 7B cost?
Gemma 3 7B is listed at $0.90 per million input tokens and $4.55 per million output tokens. Cached input is $0.12 per million tokens. A blended 3:1 input-to-output mix is about $1.81 per million tokens.
What is the context window of Gemma 3 7B?
Gemma 3 7B has a context window of 32,768 tokens and can emit up to 32,768 output tokens per request in this index.
Is Gemma 3 7B open weights?
Yes. Gemma 3 7B is listed as an open-weight model under a open weights licence.
How does Gemma 3 7B score on benchmarks?
Gemma 3 7B averages 55.9 across the scored benchmarks in this index, ranking #507 of 600 models. Its strongest relative result is Arena Elo at 1236.8.
What is Gemma 3 7B best for?
Gemma 3 7B is a small model. That makes it a good fit for classification, extraction, routing, summarization and other high-volume jobs where latency and cost dominate. It is not the right pick for open-ended frontier reasoning, but at $0.90 per million input tokens it can handle a large share of production traffic.