Gemma 3 12B IT vs Mistral Large vs Qwen2.5 7B Instruct
Gemma 3 12B IT comes out ahead, 57 to 50 and 44 on our weighted score, though Qwen2.5 7B Instruct is 17% cheaper per token.
- Our pick
Google
Gemma 3 12B IT
57/100- ECI123.5
- Price$0.05 / $0.15
- Context131K
Mistral AI
Mistral Large
44/100- ECI122.0
- Price$0.50 / $1.50
- Context128K
Alibaba (Qwen)
Qwen2.5 7B Instruct
50/100- ECI118.5
- Price$0.05 / $0.10
- Context131K
Gemma 3 12B IT is our pick
Gemma 3 12B IT is the better all-round choice, scoring 57/100 against Qwen2.5 7B Instruct (50) and Mistral Large (44). It leads on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemma 3 12B ITCapabilities Index (ECI): Gemma 3 12B IT 123.5 · Mistral Large 122.0 · Qwen2.5 7B Instruct 118.5
- Lowest priceQwen2.5 7B InstructQwen2.5 7B Instruct $0.063 · Gemma 3 12B IT $0.075 · Mistral Large $0.75 per 1M tokens (3:1 blend)
- Longest contextGemma 3 12B IT and Qwen2.5 7B InstructGemma 3 12B IT 131,072 · Qwen2.5 7B Instruct 131,072 · Mistral Large 128,000 tokens
- Widest inputsGemma 3 12B IT and Mistral LargeGemma 3 12B IT: Text, Images · Mistral Large: Text, PDFs · Qwen2.5 7B Instruct: Text
- Self-hostingGemma 3 12B IT and Qwen2.5 7B InstructPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Gemma 3 12B IT | Mistral Large | Qwen2.5 7B Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 44 | 42 | 38 |
| Price | 25% | 99 | 53 | 100 |
| Inputs & features | 15% | 50 | 45 | 25 |
| Context window | 10% | 25 | 24 | 25 |
| Overall | 100% | 57/100 | 44/100 | 50/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 123.5 (best) | 122.0 | 118.5 |
| ECI rank | #151 of 165 (best) | #153 of 165 | #159 of 165 |
| GPQA DiamondGraduate-level science questions | 39.5% (best) | 38.8% | 35.5% |
| OTIS Mock AIME 2024–2025Competition mathematics | 16.7% (best) | 1.9% | 2.5% |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.50 | $0.05 (best) |
| Output | $0.15 | $1.50 | $0.10 (best) |
| Cached input | — | $0.05 | — |
| Blended (3:1) | $0.075 | $0.75 | $0.063 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 12 providers | Official Mistral API | Median of 3 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 131,072 tokens (best) |
| Max output | 131,072 tokens (best) | 102,400 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | OpenApache 2.0 |
| API model ID | — | mistral-large-latest | — |
| API providers | 13 (best) | 11 | 4 |
| Released | Mar 12, 2025 | Feb 26, 2024 | Sep 19, 2024 |
| Knowledge cutoff | Aug 2024 | Nov 30, 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Gemma 3 12B IT$0.80
Mistral Large$8.00
Qwen2.5 7B Instruct$0.70
Which should you choose?
Which is better: Gemma 3 12B IT, Mistral Large or Qwen2.5 7B Instruct?
Gemma 3 12B IT is the better all-round choice, scoring 57/100 against Qwen2.5 7B Instruct (50) and Mistral Large (44). It leads on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemma 3 12B IT, Mistral Large or Qwen2.5 7B Instruct?
Qwen2.5 7B Instruct is cheaper at $0.05 input / $0.10 output per million tokens (median across 3 API providers). Gemma 3 12B IT costs $0.05 input / $0.15 output per million tokens (median across 12 API providers); Mistral Large costs $0.50 input / $1.50 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.063 per million tokens for Qwen2.5 7B Instruct versus $0.075 for Gemma 3 12B IT (1.2× as much) and $0.75 for Mistral Large (12× as much).
Which scores higher on benchmarks?
Gemma 3 12B IT scores higher on the Capabilities Index (ECI): Gemma 3 12B IT 123.5 (#151 of 165), Mistral Large 122.0 (#153 of 165) and Qwen2.5 7B Instruct 118.5 (#159 of 165). The confidence ranges of the top two overlap (116.9–128.4 vs 115.7–124.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemma 3 12B IT 39.5%, Mistral Large 38.8%, Qwen2.5 7B Instruct 35.5%; OTIS Mock AIME 2024–2025 — Gemma 3 12B IT 16.7%, Qwen2.5 7B Instruct 2.5%, Mistral Large 1.9%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 3 12B IT, Mistral Large and Qwen2.5 7B Instruct yet, so there is no like-for-like coding score. On overall capability, Gemma 3 12B IT leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemma 3 12B IT and Qwen2.5 7B Instruct have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Mistral Large. Maximum output per response: Gemma 3 12B IT up to 131,072, Mistral Large up to 102,400, Qwen2.5 7B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Gemma 3 12B IT accepts text and images; Mistral Large accepts text and PDFs; Qwen2.5 7B Instruct accepts text. Gemma 3 12B IT handles the widest range of inputs.
Are any of these open source?
Gemma 3 12B IT and Qwen2.5 7B Instruct publishes its weights (Apache 2.0) and can be self-hosted; Mistral Large is proprietary.
Which is newer?
Gemma 3 12B IT is the newest, released Mar 12, 2025. Qwen2.5 7B Instruct came out Sep 19, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Gemma 3 12B IT Aug 2024, Mistral Large Nov 30, 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.