Gemma 3 1.5B: pricing, context window and benchmarks
Gemma 3 1.5B is a small open-weight model from Google DeepMind. It offers a 32,768-token context window, costs $0.40 per million input tokens and $1.82 per million output tokens, and averages 48.9 across the index's benchmark suite.
Pricing
Gemma 3 1.5B costs $0.40 per million input tokens and $1.82 per million output tokens. A blended 3:1 input-to-output mix works out to about $0.76 per million tokens. Cached input is listed at $0.04 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $0.40 | per 1M tokens |
| Output | $1.82 | per 1M tokens |
| Cached input | $0.04 | per 1M tokens |
| Blended 3:1 | $0.76 | estimate per 1M tokens |
| 1M in + 1M out | $2.22 | 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 | 54.0 | 576 | 4th | |
| GPQA Diamond | 44.2 | 570 | 5th | |
| SWE-bench Verified | 32.6 | 573 | 5th | |
| HumanEval | 53.0 | 555 | 8th | |
| MATH-500 | 46.0 | 576 | 4th | |
| AIME 2025 | 39.2 | 546 | 9th | |
| LiveCodeBench | 34.0 | 573 | 5th | |
| IFEval | 62.3 | 552 | 8th | |
| TruthfulQA | 55.9 | 568 | 5th | |
| HellaSwag | 68.8 | 548 | 9th | |
| MMMU | 48.3 | 561 | 7th | |
| Arena Elo | 1193.8 | 561 | 7th |
What Gemma 3 1.5B is good for
Gemma 3 1.5B 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 $0.40 per million input tokens it can handle a large share of production traffic.
Strengths
- Input price of $0.40 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 Replicate 1.5B | Replicate | 4096 | $0.51 | 49.3 |
| Mistral Small 3 1.5B | Mistral AI | 32768 | $0.42 | 49.2 |
| Llama 3 Novita 1.5B | Novita AI | 4096 | $0.41 | 49.1 |
| Gemma 3 1.5B | Google DeepMind | 32768 | $0.40 | 48.9 |
| Llama 3 Anyscale 1.5B | Anyscale | 16384 | $0.43 | 48.9 |
| Llama 3 DeepInfra 1.5B | DeepInfra | 32768 | $0.48 | 48.8 |
FAQ
How much does Gemma 3 1.5B cost?
Gemma 3 1.5B is listed at $0.40 per million input tokens and $1.82 per million output tokens. Cached input is $0.037 per million tokens. A blended 3:1 input-to-output mix is about $0.76 per million tokens.
What is the context window of Gemma 3 1.5B?
Gemma 3 1.5B has a context window of 32,768 tokens and can emit up to 8,192 output tokens per request in this index.
Is Gemma 3 1.5B open weights?
Yes. Gemma 3 1.5B is listed as an open-weight model under a open weights licence.
How does Gemma 3 1.5B score on benchmarks?
Gemma 3 1.5B averages 48.9 across the scored benchmarks in this index, ranking #567 of 600 models. Its strongest relative result is Arena Elo at 1193.8.
What is Gemma 3 1.5B best for?
Gemma 3 1.5B 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 $0.40 per million input tokens it can handle a large share of production traffic.