Mistral Large vs Mixtral 8x22B Instruct vs Gemma 2 27B
Mistral Large comes out ahead, 44 to 35 and 34 on our weighted score, though Gemma 2 27B is 13% cheaper per token.
- Our pick
Mistral AI
Mistral Large
44/100- ECI122.0
- Price$0.50 / $1.50
- Context128K
Mistral AI
Mixtral 8x22B Instruct
34/100- ECI122.0
- Price$2.00 / $6.00
- Context66K
Google
Gemma 2 27B
35/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
Mistral Large is our pick
Mistral Large is the better all-round choice, scoring 44/100 against Gemma 2 27B (35) and Mixtral 8x22B Instruct (34). It leads on inputs & features and context window. Gemma 2 27B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemma 2 27BCapabilities Index (ECI): Gemma 2 27B 122.1 · Mistral Large 122.0 · Mixtral 8x22B Instruct 122.0
- Lowest priceGemma 2 27BGemma 2 27B $0.65 · Mistral Large $0.75 · Mixtral 8x22B Instruct $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral LargeMistral Large 128,000 · Mixtral 8x22B Instruct 65,536 · Gemma 2 27B 8,192 tokens
- Widest inputsMistral Large and Mixtral 8x22B InstructMistral Large: Text, PDFs · Mixtral 8x22B Instruct: Text, PDFs · Gemma 2 27B: Text
- Self-hostingMixtral 8x22B Instruct and Gemma 2 27BPublishes downloadable weights
| Measure | Weight | Mistral Large | Mixtral 8x22B Instruct | Gemma 2 27B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 42 | 42 | 42 |
| Price | 25% | 53 | 26 | 56 |
| Inputs & features | 15% | 45 | 35 | 0 |
| Context window | 10% | 24 | 12 | 0 |
| Overall | 100% | 44/100 | 34/100 | 35/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 122.0 | 122.0 | 122.1 (best) |
| ECI rank | #153 of 165 | #155 of 165 | #152 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 38.8% (best) | 34.1% | 36.5% |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.9% (best) | — | 1.4% |
| Price per million tokens | |||
| Input | $0.50 (best) | $2.00 | $0.65 |
| Output | $1.50 | $6.00 | $0.65 (best) |
| Cached input | $0.05 | — | — |
| Blended (3:1) | $0.75 | $3.00 | $0.65 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 5 providers | Median of 3 providers |
| Limits | |||
| Context window | 128,000 tokens (best) | 65,536 tokens | 8,192 tokens |
| Max output | 102,400 tokens (best) | 52,428 tokens | 2,048 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | Yes | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | No |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | mistral-large-latest | — | — |
| API providers | 11 (best) | 5 | 3 |
| Released | Feb 26, 2024 | Apr 17, 2024 | Jul 13, 2024 |
| Knowledge cutoff | Nov 30, 2024 | Jan 31, 2024 | Jun 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.
Mistral Large$8.00
Mixtral 8x22B Instruct$32.00
Gemma 2 27B$7.80
Which should you choose?
Which is better: Mistral Large, Mixtral 8x22B Instruct or Gemma 2 27B?
Mistral Large is the better all-round choice, scoring 44/100 against Gemma 2 27B (35) and Mixtral 8x22B Instruct (34). It leads on inputs & features and context window. Gemma 2 27B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Large, Mixtral 8x22B Instruct or Gemma 2 27B?
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); Mixtral 8x22B Instruct costs $2.00 input / $6.00 output per million tokens (median across 5 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 Mixtral 8x22B Instruct (4.6× as much).
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 Mixtral 8x22B Instruct 122.0 (#155 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%, Mixtral 8x22B Instruct 34.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large, Mixtral 8x22B Instruct and Gemma 2 27B 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 65,536 for Mixtral 8x22B Instruct and 8,192 for Gemma 2 27B. Maximum output per response: Mistral Large up to 102,400, Mixtral 8x22B Instruct up to 52,428, Gemma 2 27B up to 2,048 tokens.
Which can read images, PDFs, audio or video?
Mistral Large accepts text and PDFs; Mixtral 8x22B Instruct accepts text and PDFs; Gemma 2 27B accepts text. Mistral Large handles the widest range of inputs.
Are any of these open source?
Mixtral 8x22B Instruct and Gemma 2 27B publishes its weights and can be self-hosted; Mistral Large is proprietary.
Which is newer?
Gemma 2 27B is the newest, released Jul 13, 2024. Mixtral 8x22B Instruct came out Apr 17, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Mistral Large Nov 30, 2024, Mixtral 8x22B Instruct Jan 31, 2024, Gemma 2 27B Jun 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.