Gemma 3 8B: pricing, context window and benchmarks
Gemma 3 8B is a small open-weight model from Google DeepMind. It offers a 16,384-token context window, costs $0.96 per million input tokens and $4.88 per million output tokens, and averages 56.5 across the index's benchmark suite.
Pricing
Gemma 3 8B costs $0.96 per million input tokens and $4.88 per million output tokens. A blended 3:1 input-to-output mix works out to about $1.94 per million tokens. Cached input is listed at $0.11 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $0.96 | per 1M tokens |
| Output | $4.88 | per 1M tokens |
| Cached input | $0.11 | per 1M tokens |
| Blended 3:1 | $1.94 | estimate per 1M tokens |
| 1M in + 1M out | $5.84 | 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 | 64.1 | 467 | 22th | |
| GPQA Diamond | 50.4 | 519 | 14th | |
| SWE-bench Verified | 41.7 | 502 | 16th | |
| HumanEval | 61.6 | 471 | 22th | |
| MATH-500 | 58.8 | 479 | 20th | |
| AIME 2025 | 43.5 | 516 | 14th | |
| LiveCodeBench | 46.8 | 478 | 20th | |
| IFEval | 67.3 | 498 | 17th | |
| TruthfulQA | 63.1 | 487 | 19th | |
| HellaSwag | 70.8 | 525 | 13th | |
| MMMU | 53.0 | 518 | 14th | |
| Arena Elo | 1248.2 | 493 | 18th |
What Gemma 3 8B is good for
Gemma 3 8B 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 $0.96 per million input tokens it can handle a large share of production traffic.
Strengths
- Input price of $0.96 per million tokens is at or below the index median.
- Open weights make self-hosting, fine-tuning and data-residency review possible.
Trade-offs
- Context window of 16,384 tokens is small for long-document work.
- 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 3.3 Groq 7B | Groq | 16384 | $1.01 | 56.7 |
| DeepSeek-R1 1.5B | DeepSeek | 16384 | $1.04 | 56.6 |
| Llama 3 Modal 8B | Modal | 32768 | $0.98 | 56.6 |
| Gemma 3 8B | Google DeepMind | 16384 | $0.96 | 56.5 |
| Llama 3.1 Cerebras 7B | Cerebras | 32768 | $0.95 | 56.5 |
| Llama 3.1 Turbo 7B | Together AI | 8192 | $0.98 | 56.4 |
FAQ
How much does Gemma 3 8B cost?
Gemma 3 8B is listed at $0.96 per million input tokens and $4.88 per million output tokens. Cached input is $0.11 per million tokens. A blended 3:1 input-to-output mix is about $1.94 per million tokens.
What is the context window of Gemma 3 8B?
Gemma 3 8B has a context window of 16,384 tokens and can emit up to 16,384 output tokens per request in this index.
Is Gemma 3 8B open weights?
Yes. Gemma 3 8B is listed as an open-weight model under a open weights licence.
How does Gemma 3 8B score on benchmarks?
Gemma 3 8B averages 56.5 across the scored benchmarks in this index, ranking #498 of 600 models. Its strongest relative result is Arena Elo at 1248.2.
What is Gemma 3 8B best for?
Gemma 3 8B 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 $0.96 per million input tokens it can handle a large share of production traffic.