Gemma 2 27B vs Mistral 7B Instruct v0.3 vs Mistral Large
Mistral Large comes out ahead, 40 to 28 and 22 on our weighted score, though Gemma 2 27B is 13% cheaper per token.
GoogleGemma 2 27B
28/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
Mistral AIMistral 7B Instruct v0.3
22/100- ECI109.0
- Price—
- Context33K
- Our pickMistral AI
Mistral Large
40/100- ECI122.0
- Price$0.50 / $1.50
- Context128K
Mistral Large is our pick
Mistral Large is the better all-round choice, scoring 40/100 against Gemma 2 27B (28) and Mistral 7B Instruct v0.3 (22). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityGemma 2 27BCapabilities Index (ECI): Gemma 2 27B 122.1 · Mistral Large 122.0 · Mistral 7B Instruct v0.3 109.0
- Lowest priceGemma 2 27BGemma 2 27B $0.65 · Mistral Large $0.75 per 1M tokens (3:1 blend) · Mistral 7B Instruct v0.3 unpriced
- Longest contextMistral LargeMistral Large 128,000 · Mistral 7B Instruct v0.3 32,768 · Gemma 2 27B 8,192 tokens
- Widest inputsMistral LargeGemma 2 27B: Text · Mistral 7B Instruct v0.3: Text · Mistral Large: Text, PDFs
- Self-hostingGemma 2 27B and Mistral 7B Instruct v0.3Publishes downloadable weights (Apache 2.0)
| Measure | Weight | Gemma 2 27B | Mistral 7B Instruct v0.3 | Mistral Large |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 42 | 26 | 42 |
| Inputs & features | 20% | 0 | 25 | 45 |
| Context window | 13% | 0 | 0 | 24 |
| Overall | 100% | 28/100 | 22/100 | 40/100 |
Left out because at least one model lacks the data: price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemma 2 27BGoogle | Mistral 7B Instruct v0.3Mistral AI | Mistral LargeMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 122.1 (best) | 109.0 | 122.0 |
| ECI rank | #152 of 165 (best) | #164 of 165 | #153 of 165 |
| GPQA DiamondGraduate-level science questions | 36.5% | 15.2% | 38.8% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.4% | 0.3% | 1.9% (best) |
| Price per million tokens | |||
| Input | $0.65 | — | $0.50 (best) |
| Output | $0.65 (best) | — | $1.50 |
| Cached input | — | — | $0.05 |
| Blended (3:1) | $0.65 (best) | — | $0.75 |
| Long-context rate | Same rate | — | Same rate |
| Price source | Median of 3 providers | — | Official Mistral API |
| Limits | |||
| Context window | 8,192 tokens | 32,768 tokens | 128,000 tokens (best) |
| Max output | 2,048 tokens | 32,768 tokens | 102,400 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Proprietary |
| API model ID | — | — | mistral-large-latest |
| API providers | 3 | 1 | 11 (best) |
| Released | Jul 13, 2024 | May 22, 2024 | Feb 26, 2024 |
| Knowledge cutoff | Jun 30, 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 2 27B$7.80
- Mistral 7B Instruct v0.3—
- Mistral Large$8.00
Which should you choose?
Which is better: Gemma 2 27B, Mistral 7B Instruct v0.3 or Mistral Large?
Mistral Large is the better all-round choice, scoring 40/100 against Gemma 2 27B (28) and Mistral 7B Instruct v0.3 (22). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Gemma 2 27B, Mistral 7B Instruct v0.3 or Mistral Large?
Gemma 2 27B is cheaper at $0.65 input / $0.65 output per million tokens (median across 3 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 $0.65 per million tokens for Gemma 2 27B versus $0.75 for Mistral Large (1.2× as much). Mistral 7B Instruct v0.3 has no published per-token price.
Which scores higher on benchmarks?
Gemma 2 27B scores higher on the Capabilities Index (ECI): Gemma 2 27B 122.1 (#152 of 165), Mistral Large 122.0 (#153 of 165) and Mistral 7B Instruct v0.3 109.0 (#164 of 165). The confidence ranges of the top two overlap (115.8–124.1 vs 115.7–124.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 38.8%, Gemma 2 27B 36.5%, Mistral 7B Instruct v0.3 15.2%; OTIS Mock AIME 2024–2025 — Mistral Large 1.9%, Gemma 2 27B 1.4%, Mistral 7B Instruct v0.3 0.3%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 2 27B, Mistral 7B Instruct v0.3 and Mistral Large yet, so there is no like-for-like coding score. On overall capability, Gemma 2 27B leads, which tends to carry over to coding, but test on your own codebase. Note that Gemma 2 27B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Mistral Large has the largest context window at 128,000 tokens, against 32,768 for Mistral 7B Instruct v0.3 and 8,192 for Gemma 2 27B. Maximum output per response: Gemma 2 27B up to 2,048, Mistral 7B Instruct v0.3 up to 32,768, Mistral Large up to 102,400 tokens.
Which can read images, PDFs, audio or video?
Gemma 2 27B accepts text; Mistral 7B Instruct v0.3 accepts text; Mistral Large accepts text and PDFs. Mistral Large handles the widest range of inputs.
Are any of these open source?
Gemma 2 27B and Mistral 7B Instruct v0.3 publishes its weights (Apache 2.0) and can be self-hosted; Mistral Large is proprietary.
Which is newer?
Gemma 2 27B is the newest, released Jul 13, 2024. Mistral 7B Instruct v0.3 came out May 22, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Gemma 2 27B Jun 30, 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.
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