Claude Haiku 3 vs Mixtral 8x7B Instruct v0.1 vs Gemma 2 27B
Claude Haiku 3 comes out ahead, 46 to 35 and 34 on our weighted score.
- Our pick
AnthropicClaude Haiku 3
46/100- ECI118.8
- Price$0.25 / $1.25
- Context200K
Mistral AIMixtral 8x7B Instruct v0.1
34/100- ECI118.4
- Price$0.444 / $0.579
- Context33K
GoogleGemma 2 27B
35/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
Claude Haiku 3 is our pick
Claude Haiku 3 is the better all-round choice, scoring 46/100 against Gemma 2 27B (35) and Mixtral 8x7B Instruct v0.1 (34). It leads on inputs & features and context window. Gemma 2 27B wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemma 2 27BCapabilities Index (ECI): Gemma 2 27B 122.1 · Claude Haiku 3 118.8 · Mixtral 8x7B Instruct v0.1 118.4
- Lowest priceMixtral 8x7B Instruct v0.1Mixtral 8x7B Instruct v0.1 $0.478 · Claude Haiku 3 $0.50 · Gemma 2 27B $0.65 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 3Claude Haiku 3 200,000 · Mixtral 8x7B Instruct v0.1 32,768 · Gemma 2 27B 8,192 tokens
- Widest inputsClaude Haiku 3Claude Haiku 3: Text, Images, PDFs · Mixtral 8x7B Instruct v0.1: Text · Gemma 2 27B: Text
- Self-hostingMixtral 8x7B Instruct v0.1 and Gemma 2 27BPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Claude Haiku 3 | Mixtral 8x7B Instruct v0.1 | Gemma 2 27B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 38 | 38 | 42 |
| Price | 25% | 61 | 62 | 56 |
| Inputs & features | 15% | 60 | 0 | 0 |
| Context window | 10% | 32 | 0 | 0 |
| Overall | 100% | 46/100 | 34/100 | 35/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Claude Haiku 3Anthropic | Mixtral 8x7B Instruct v0.1Mistral AI | Gemma 2 27BGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 118.8 | 118.4 | 122.1 (best) |
| ECI rank | #156 of 165 | #160 of 165 | #152 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 36.3% | 30.6% | 36.5% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.8% (best) | — | 1.4% |
| Price per million tokens | |||
| Input | $0.25 (best) | $0.444 | $0.65 |
| Output | $1.25 | $0.579 (best) | $0.65 |
| Cached input | — | — | — |
| Blended (3:1) | $0.50 | $0.478 (best) | $0.65 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 2 providers | Median of 3 providers |
| Limits | |||
| Context window | 200,000 tokens (best) | 32,768 tokens | 8,192 tokens |
| Max output | 4,096 tokens | 32,768 tokens (best) | 2,048 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | 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 | No | No | No |
| Availability | |||
| Weights | Proprietary | OpenApache 2.0 | Open |
| API model ID | — | — | — |
| API providers | 3 (best) | 2 | 3 (best) |
| Released | Mar 13, 2024 | Dec 11, 2023 | Jul 13, 2024 |
| Knowledge cutoff | Aug 31, 2023 | — | 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.
- Claude Haiku 3$5.00
- Mixtral 8x7B Instruct v0.1$5.60
- Gemma 2 27B$7.80
Which should you choose?
Which is better: Claude Haiku 3, Mixtral 8x7B Instruct v0.1 or Gemma 2 27B?
Claude Haiku 3 is the better all-round choice, scoring 46/100 against Gemma 2 27B (35) and Mixtral 8x7B Instruct v0.1 (34). It leads on inputs & features and context window. Gemma 2 27B wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Claude Haiku 3, Mixtral 8x7B Instruct v0.1 or Gemma 2 27B?
Mixtral 8x7B Instruct v0.1 is cheaper at $0.444 input / $0.579 output per million tokens (median across 2 API providers). Claude Haiku 3 costs $0.25 input / $1.25 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). At a typical mix of three input tokens to one output token, that is $0.478 per million tokens for Mixtral 8x7B Instruct v0.1 versus $0.50 for Claude Haiku 3 (1× as much) and $0.65 for Gemma 2 27B (1.4× 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), Claude Haiku 3 118.8 (#156 of 165) and Mixtral 8x7B Instruct v0.1 118.4 (#160 of 165). The confidence ranges of the top two overlap (115.8–124.1 vs 111.7–121.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemma 2 27B 36.5%, Claude Haiku 3 36.3%, Mixtral 8x7B Instruct v0.1 30.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 3, Mixtral 8x7B Instruct v0.1 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 Mixtral 8x7B Instruct v0.1 and Gemma 2 27B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Claude Haiku 3 has the largest context window at 200,000 tokens, against 32,768 for Mixtral 8x7B Instruct v0.1 and 8,192 for Gemma 2 27B. Maximum output per response: Claude Haiku 3 up to 4,096, Mixtral 8x7B Instruct v0.1 up to 32,768, Gemma 2 27B up to 2,048 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 3 accepts text, images and PDFs; Mixtral 8x7B Instruct v0.1 accepts text; Gemma 2 27B accepts text. Claude Haiku 3 handles the widest range of inputs.
Are any of these open source?
Mixtral 8x7B Instruct v0.1 and Gemma 2 27B publishes its weights (Apache 2.0) and can be self-hosted; Claude Haiku 3 is proprietary.
Which is newer?
Gemma 2 27B is the newest, released Jul 13, 2024. Claude Haiku 3 came out Mar 13, 2024; Mixtral 8x7B Instruct v0.1 came out Dec 11, 2023. Knowledge cutoff: Claude Haiku 3 Aug 31, 2023, 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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