Mixtral 8x22B Instruct vs Mistral 7B Instruct v0.3 vs Gemma 2 27B
Mixtral 8x22B Instruct comes out ahead, 37 to 28 and 22 on our weighted score, though Gemma 2 27B is 4.6× cheaper per token.
- Our pick
Mistral AIMixtral 8x22B Instruct
37/100- ECI122.0
- Price$2.00 / $6.00
- Context66K
- Mistral AI
Mistral 7B Instruct v0.3
22/100- ECI109.0
- Price—
- Context33K
GoogleGemma 2 27B
28/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
Mixtral 8x22B Instruct is our pick
Mixtral 8x22B Instruct is the better all-round choice, scoring 37/100 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 · Mixtral 8x22B Instruct 122.0 · Mistral 7B Instruct v0.3 109.0
- Lowest priceGemma 2 27BGemma 2 27B $0.65 · Mixtral 8x22B Instruct $3.00 per 1M tokens (3:1 blend) · Mistral 7B Instruct v0.3 unpriced
- Longest contextMixtral 8x22B InstructMixtral 8x22B Instruct 65,536 · Mistral 7B Instruct v0.3 32,768 · Gemma 2 27B 8,192 tokens
- Widest inputsMixtral 8x22B InstructMixtral 8x22B Instruct: Text, PDFs · Mistral 7B Instruct v0.3: Text · Gemma 2 27B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mixtral 8x22B Instruct | Mistral 7B Instruct v0.3 | Gemma 2 27B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 42 | 26 | 42 |
| Inputs & features | 20% | 35 | 25 | 0 |
| Context window | 13% | 12 | 0 | 0 |
| Overall | 100% | 37/100 | 22/100 | 28/100 |
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 | Mixtral 8x22B InstructMistral AI | Mistral 7B Instruct v0.3Mistral AI | Gemma 2 27BGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 122.0 | 109.0 | 122.1 (best) |
| ECI rank | #155 of 165 | #164 of 165 | #152 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 34.1% | 15.2% | 36.5% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 0.3% | 1.4% (best) |
| Price per million tokens | |||
| Input | $2.00 | — | $0.65 (best) |
| Output | $6.00 | — | $0.65 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $3.00 | — | $0.65 (best) |
| Long-context rate | Same rate | — | Same rate |
| Price source | Median of 5 providers | — | Median of 3 providers |
| Limits | |||
| Context window | 65,536 tokens (best) | 32,768 tokens | 8,192 tokens |
| Max output | 52,428 tokens (best) | 32,768 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 | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Open |
| API model ID | — | — | — |
| API providers | 5 (best) | 1 | 3 |
| Released | Apr 17, 2024 | May 22, 2024 | Jul 13, 2024 |
| Knowledge cutoff | 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.
- Mixtral 8x22B Instruct$32.00
- Mistral 7B Instruct v0.3—
- Gemma 2 27B$7.80
Which should you choose?
Which is better: Mixtral 8x22B Instruct, Mistral 7B Instruct v0.3 or Gemma 2 27B?
Mixtral 8x22B Instruct is the better all-round choice, scoring 37/100 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, Mixtral 8x22B Instruct, Mistral 7B Instruct v0.3 or Gemma 2 27B?
Gemma 2 27B is cheaper at $0.65 input / $0.65 output per million tokens (median across 3 API providers). 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 $3.00 for Mixtral 8x22B Instruct (4.6× 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), Mixtral 8x22B Instruct 122.0 (#155 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 115.7–124.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemma 2 27B 36.5%, Mixtral 8x22B Instruct 34.1%, Mistral 7B Instruct v0.3 15.2%.
Which is better for coding?
There are no published SWE-bench Verified results for Mixtral 8x22B Instruct, Mistral 7B Instruct v0.3 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?
Mixtral 8x22B Instruct has the largest context window at 65,536 tokens, against 32,768 for Mistral 7B Instruct v0.3 and 8,192 for Gemma 2 27B. Maximum output per response: Mixtral 8x22B Instruct up to 52,428, Mistral 7B Instruct v0.3 up to 32,768, Gemma 2 27B up to 2,048 tokens.
Which can read images, PDFs, audio or video?
Mixtral 8x22B Instruct accepts text and PDFs; Mistral 7B Instruct v0.3 accepts text; Gemma 2 27B accepts text. Mixtral 8x22B Instruct handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Gemma 2 27B is the newest, released Jul 13, 2024. Mistral 7B Instruct v0.3 came out May 22, 2024; Mixtral 8x22B Instruct came out Apr 17, 2024. Knowledge cutoff: 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.
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