Gemma 2 27B vs Mistral Large vs Mistral Large 2.1
Mistral Large comes out ahead, 44 to 38 and 35 on our weighted score, though Gemma 2 27B is 13% cheaper per token.
GoogleGemma 2 27B
35/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
- Our pick
Mistral AIMistral Large
44/100- ECI122.0
- Price$0.50 / $1.50
- Context128K
- Mistral AI
Mistral Large 2.1
38/100- ECI128.6
- Price$2.00 / $6.00
- Context131K
Mistral Large is our pick
Mistral Large is the better all-round choice, scoring 44/100 against Mistral Large 2.1 (38) and Gemma 2 27B (35). It leads on inputs & features. Gemma 2 27B wins on price. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral Large 2.1Capabilities Index (ECI): Mistral Large 2.1 128.6 · Gemma 2 27B 122.1 · Mistral Large 122.0
- Lowest priceGemma 2 27BGemma 2 27B $0.65 · Mistral Large $0.75 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral Large 2.1Mistral Large 2.1 131,072 · Mistral Large 128,000 · Gemma 2 27B 8,192 tokens
- Widest inputsMistral LargeGemma 2 27B: Text · Mistral Large: Text, PDFs · Mistral Large 2.1: Text
- Self-hostingGemma 2 27B and Mistral Large 2.1Publishes downloadable weights
| Measure | Weight | Gemma 2 27B | Mistral Large | Mistral Large 2.1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 42 | 42 | 50 |
| Price | 25% | 56 | 53 | 26 |
| Inputs & features | 15% | 0 | 45 | 25 |
| Context window | 10% | 0 | 24 | 25 |
| Overall | 100% | 35/100 | 44/100 | 38/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemma 2 27BGoogle | Mistral LargeMistral AI | Mistral Large 2.1Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 122.1 | 122.0 | 128.6 (best) |
| ECI rank | #152 of 165 | #153 of 165 | #142 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 36.5% | 38.8% | 51.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.4% | 1.9% | 7.8% (best) |
| Price per million tokens | |||
| Input | $0.65 | $0.50 (best) | $2.00 |
| Output | $0.65 (best) | $1.50 | $6.00 |
| Cached input | — | $0.05 | — |
| Blended (3:1) | $0.65 (best) | $0.75 | $3.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official Mistral API | Median of 2 providers |
| Limits | |||
| Context window | 8,192 tokens | 128,000 tokens | 131,072 tokens (best) |
| Max output | 2,048 tokens | 102,400 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | — | mistral-large-latest | — |
| API providers | 3 | 11 (best) | 2 |
| Released | Jul 13, 2024 | Feb 26, 2024 | Nov 18, 2024 |
| Knowledge cutoff | Jun 30, 2024 | Nov 30, 2024 | Nov 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 Large$8.00
- Mistral Large 2.1$32.00
Which should you choose?
Which is better: Gemma 2 27B, Mistral Large or Mistral Large 2.1?
Mistral Large is the better all-round choice, scoring 44/100 against Mistral Large 2.1 (38) and Gemma 2 27B (35). It leads on inputs & features. Gemma 2 27B wins on price. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemma 2 27B, Mistral Large or Mistral Large 2.1?
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); Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (median across 2 API providers). 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) and $3.00 for Mistral Large 2.1 (4.6× as much).
Which scores higher on benchmarks?
Mistral Large 2.1 scores higher on the Capabilities Index (ECI): Mistral Large 2.1 128.6 (#142 of 165), Gemma 2 27B 122.1 (#152 of 165) and Mistral Large 122.0 (#153 of 165). Their confidence ranges do not overlap (124.3–130.7 vs 115.8–124.1), so the gap is a real one. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Mistral Large 38.8%, Gemma 2 27B 36.5%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Mistral Large 1.9%, Gemma 2 27B 1.4%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 2 27B, Mistral Large and Mistral Large 2.1 yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2.1 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 2.1 has the largest context window at 131,072 tokens, against 128,000 for Mistral Large and 8,192 for Gemma 2 27B. Maximum output per response: Gemma 2 27B up to 2,048, Mistral Large up to 102,400, Mistral Large 2.1 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Gemma 2 27B accepts text; Mistral Large accepts text and PDFs; Mistral Large 2.1 accepts text. Mistral Large handles the widest range of inputs.
Are any of these open source?
Gemma 2 27B and Mistral Large 2.1 publishes its weights and can be self-hosted; Mistral Large is proprietary.
Which is newer?
Mistral Large 2.1 is the newest, released Nov 18, 2024. Gemma 2 27B came out Jul 13, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Gemma 2 27B Jun 30, 2024, Mistral Large Nov 30, 2024, Mistral Large 2.1 Nov 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.
