Mixtral 8x7B vs Qwen Plus Character (Japanese) vs Claude Haiku 3
Claude Haiku 3 comes out ahead, 56 to 36 and 36 on our weighted score, and it is the cheaper option too.
Mistral AIMixtral 8x7B
36/100- ECI118.5
- Price$0.70 / $0.70
- Context32K
Alibaba (Qwen)Qwen Plus Character (Japanese)
36/100- ECI—
- Price$0.50 / $1.40
- Context8K
- Our pick
AnthropicClaude Haiku 3
56/100- ECI118.4
- Price$0.25 / $1.25
- Context200K
Claude Haiku 3 is our pick
Claude Haiku 3 is the better all-round choice, scoring 56/100 against Mixtral 8x7B (36) and Qwen Plus Character (Japanese) (36). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceClaude Haiku 3Claude Haiku 3 $0.50 · Mixtral 8x7B $0.70 · Qwen Plus Character (Japanese) $0.725 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 3Claude Haiku 3 200,000 · Mixtral 8x7B 32,000 · Qwen Plus Character (Japanese) 8,192 tokens
- Widest inputsClaude Haiku 3Mixtral 8x7B: Text · Qwen Plus Character (Japanese): Text · Claude Haiku 3: Text, Images, PDFs
- Self-hostingMixtral 8x7BPublishes downloadable weights
| Measure | Weight | Mixtral 8x7B | Qwen Plus Character (Japanese) | Claude Haiku 3 |
|---|---|---|---|---|
| Price | 50% | 57 | 57 | 64 |
| Inputs & features | 30% | 25 | 25 | 60 |
| Context window | 20% | 0 | 0 | 32 |
| Overall | 100% | 36/100 | 36/100 | 56/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mixtral 8x7BMistral AI | Qwen Plus Character (Japanese)Alibaba (Qwen) | Claude Haiku 3Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 118.5 (best) | — | 118.4 |
| ECI rank | #142 of 148 (best) | — | #143 of 148 |
| GPQA DiamondGraduate-level science questions | 30.6% | — | 36.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 1.8% |
| Price per million tokens | |||
| Input | $0.70 | $0.50 | $0.25 (best) |
| Output | $0.70 (best) | $1.40 | $1.25 |
| Cached input | — | — | — |
| Blended (3:1) | $0.70 | $0.725 | $0.50 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Alibaba API | Median of 2 providers |
| Limits | |||
| Context window | 32,000 tokens | 8,192 tokens | 200,000 tokens (best) |
| Max output | 32,000 tokens (best) | 512 tokens | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | open-mixtral-8x7b | qwen-plus-character-ja | — |
| API providers | 1 | 1 | 2 (best) |
| Released | Dec 11, 2023 | Jan 2024 | Mar 13, 2024 |
| Knowledge cutoff | Jan 2024 | Apr 2024 | Aug 31, 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mixtral 8x7B$8.40
- Qwen Plus Character (Japanese)$7.80
- Claude Haiku 3$5.00
Which should you choose?
Which is better: Mixtral 8x7B, Qwen Plus Character (Japanese) or Claude Haiku 3?
Claude Haiku 3 is the better all-round choice, scoring 56/100 against Mixtral 8x7B (36) and Qwen Plus Character (Japanese) (36). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Mixtral 8x7B, Qwen Plus Character (Japanese) or Claude Haiku 3?
Claude Haiku 3 is cheaper at $0.25 input / $1.25 output per million tokens (median across 2 API providers). Mixtral 8x7B costs $0.70 input / $0.70 output per million tokens (official Mistral API price); Qwen Plus Character (Japanese) costs $0.50 input / $1.40 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.50 per million tokens for Claude Haiku 3 versus $0.70 for Mixtral 8x7B (1.4× as much) and $0.725 for Qwen Plus Character (Japanese) (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Mixtral 8x7B has an ECI of 118.5, Qwen Plus Character (Japanese) has not been scored yet and Claude Haiku 3 has an ECI of 118.4.
Which is better for coding?
There are no published SWE-bench Verified results for Mixtral 8x7B, Qwen Plus Character (Japanese) and Claude Haiku 3 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Claude Haiku 3 has the largest context window at 200,000 tokens, against 32,000 for Mixtral 8x7B and 8,192 for Qwen Plus Character (Japanese). Maximum output per response: Mixtral 8x7B up to 32,000, Qwen Plus Character (Japanese) up to 512, Claude Haiku 3 up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Mixtral 8x7B accepts text; Qwen Plus Character (Japanese) accepts text; Claude Haiku 3 accepts text, images and PDFs. Claude Haiku 3 handles the widest range of inputs.
Are any of these open source?
Mixtral 8x7B publishes its weights and can be self-hosted; Qwen Plus Character (Japanese) and Claude Haiku 3 is proprietary.
Which is newer?
Claude Haiku 3 is the newest, released Mar 13, 2024. Qwen Plus Character (Japanese) came out Jan 2024; Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Mixtral 8x7B Jan 2024, Qwen Plus Character (Japanese) Apr 2024, Claude Haiku 3 Aug 31, 2023.
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 Oct 4, 2026.
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