Mistral Large vs WizardLM 2 8x22B vs Gemma 2 27B
Mistral Large comes out ahead, 42 to 38 and 32 on our weighted score, though WizardLM 2 8x22B is 34% cheaper per token.
- Our pick
Mistral AI
Mistral Large
42/100- ECI122.0
- Price$0.50 / $1.50
- Context128K
Microsoft
WizardLM 2 8x22B
38/100- ECI—
- Price$0.493 / $0.493
- Context66K
Google
Gemma 2 27B
32/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
Mistral Large is our pick
Mistral Large is the better all-round choice, scoring 42/100 against WizardLM 2 8x22B (38) and Gemma 2 27B (32). It leads on inputs & features and context window. WizardLM 2 8x22B wins on capability and price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because WizardLM 2 8x22B has no Capabilities Index score yet.
- CapabilityWizardLM 2 8x22BShared benchmarks: WizardLM 2 8x22B 43.4% · Mistral Large 38.8% · Gemma 2 27B 36.5%
- Lowest priceWizardLM 2 8x22BWizardLM 2 8x22B $0.493 · Gemma 2 27B $0.65 · Mistral Large $0.75 per 1M tokens (3:1 blend)
- Longest contextMistral LargeMistral Large 128,000 · WizardLM 2 8x22B 65,536 · Gemma 2 27B 8,192 tokens
- Widest inputsMistral LargeMistral Large: Text, PDFs · WizardLM 2 8x22B: Text · Gemma 2 27B: Text
- Self-hostingWizardLM 2 8x22B and Gemma 2 27BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Mistral Large | WizardLM 2 8x22B | Gemma 2 27B |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 39 | 43 | 36 |
| Price | 25% | 53 | 62 | 56 |
| Inputs & features | 15% | 45 | 0 | 0 |
| Context window | 10% | 24 | 12 | 0 |
| Overall | 100% | 42/100 | 38/100 | 32/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 122.0 | — | 122.1 (best) |
| ECI rank | #153 of 165 | — | #152 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 38.8% | 43.4% (best) | 36.5% |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.9% (best) | — | 1.4% |
| Price per million tokens | |||
| Input | $0.50 | $0.493 (best) | $0.65 |
| Output | $1.50 | $0.493 (best) | $0.65 |
| Cached input | $0.05 | — | — |
| Blended (3:1) | $0.75 | $0.493 (best) | $0.65 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 3 providers | Median of 3 providers |
| Limits | |||
| Context window | 128,000 tokens (best) | 65,536 tokens | 8,192 tokens |
| Max output | 102,400 tokens (best) | 8,000 tokens | 2,048 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | No | No |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | OpenApache-2.0 | Open |
| API model ID | mistral-large-latest | — | — |
| API providers | 11 (best) | 3 | 3 |
| Released | Feb 26, 2024 | Apr 15, 2024 | Jul 13, 2024 |
| Knowledge cutoff | Nov 30, 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
WizardLM 2 8x22B$5.92
Gemma 2 27B$7.80
Which should you choose?
Which is better: Mistral Large, WizardLM 2 8x22B or Gemma 2 27B?
Mistral Large is the better all-round choice, scoring 42/100 against WizardLM 2 8x22B (38) and Gemma 2 27B (32). It leads on inputs & features and context window. WizardLM 2 8x22B wins on capability and price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because WizardLM 2 8x22B has no Capabilities Index score yet.
Which is cheaper, Mistral Large, WizardLM 2 8x22B or Gemma 2 27B?
WizardLM 2 8x22B is cheaper at $0.493 input / $0.493 output per million tokens (median across 3 API providers). Gemma 2 27B costs $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 $0.493 per million tokens for WizardLM 2 8x22B versus $0.65 for Gemma 2 27B (1.3× as much) and $0.75 for Mistral Large (1.5× as much).
Which scores higher on benchmarks?
Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond): WizardLM 2 8x22B 43.4%, Mistral Large 38.8% and Gemma 2 27B 36.5%. On individual benchmarks: GPQA Diamond — WizardLM 2 8x22B 43.4%, Mistral Large 38.8%, Gemma 2 27B 36.5%.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large, WizardLM 2 8x22B and Gemma 2 27B yet, so there is no like-for-like coding score. On overall capability, WizardLM 2 8x22B leads, which tends to carry over to coding, but test on your own codebase. Note that WizardLM 2 8x22B and 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 WizardLM 2 8x22B and 8,192 for Gemma 2 27B. Maximum output per response: Mistral Large up to 102,400, WizardLM 2 8x22B up to 8,000, Gemma 2 27B up to 2,048 tokens.
Which can read images, PDFs, audio or video?
Mistral Large accepts text and PDFs; WizardLM 2 8x22B accepts text; Gemma 2 27B accepts text. Mistral Large handles the widest range of inputs.
Are any of these open source?
WizardLM 2 8x22B and Gemma 2 27B 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. WizardLM 2 8x22B came out Apr 15, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Mistral Large Nov 30, 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.