Claude Haiku 3.5 vs Mixtral 8x22B Instruct vs Mistral Large 2.1
Claude Haiku 3.5 comes out ahead, 46 to 38 and 34 on our weighted score, and it is the cheaper option too.
- Our pick
Anthropic
Claude Haiku 3.5
46/100- ECI127.0
- Price$0.80 / $4.00
- Context200K
Mistral AI
Mixtral 8x22B Instruct
34/100- ECI122.0
- Price$2.00 / $6.00
- Context66K
Mistral AI
Mistral Large 2.1
38/100- ECI128.6
- Price$2.00 / $6.00
- Context131K
Claude Haiku 3.5 is our pick
Claude Haiku 3.5 is the better all-round choice, scoring 46/100 against Mistral Large 2.1 (38) and Mixtral 8x22B Instruct (34). It leads on price, inputs & features and context window. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral Large 2.1Capabilities Index (ECI): Mistral Large 2.1 128.6 · Claude Haiku 3.5 127.0 · Mixtral 8x22B Instruct 122.0
- Lowest priceClaude Haiku 3.5Claude Haiku 3.5 $1.60 · Mixtral 8x22B Instruct $3.00 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Mistral Large 2.1 131,072 · Mixtral 8x22B Instruct 65,536 tokens
- Widest inputsClaude Haiku 3.5Claude Haiku 3.5: Text, Images, PDFs · Mixtral 8x22B Instruct: Text, PDFs · Mistral Large 2.1: Text
- Self-hostingMixtral 8x22B Instruct and Mistral Large 2.1Publishes downloadable weights
| Measure | Weight | Claude Haiku 3.5 | Mixtral 8x22B Instruct | Mistral Large 2.1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 48 | 42 | 50 |
| Price | 25% | 38 | 26 | 26 |
| Inputs & features | 15% | 60 | 35 | 25 |
| Context window | 10% | 32 | 12 | 25 |
| Overall | 100% | 46/100 | 34/100 | 38/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 127.0 | 122.0 | 128.6 (best) |
| ECI rank | #147 of 165 | #155 of 165 | #142 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 38.1% | 34.1% | 51.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 4.3% | — | 7.8% (best) |
| Price per million tokens | |||
| Input | $0.80 (best) | $2.00 | $2.00 |
| Output | $4.00 (best) | $6.00 | $6.00 |
| Cached input | — | — | — |
| Blended (3:1) | $1.60 (best) | $3.00 | $3.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 5 providers | Median of 2 providers |
| Limits | |||
| Context window | 200,000 tokens (best) | 65,536 tokens | 131,072 tokens |
| Max output | 8,192 tokens | 52,428 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | — | — | — |
| API providers | 4 | 5 (best) | 2 |
| Released | Oct 22, 2024 | Apr 17, 2024 | Nov 18, 2024 |
| Knowledge cutoff | Jul 31, 2024 | Jan 31, 2024 | Nov 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$16.00
Mixtral 8x22B Instruct$32.00
Mistral Large 2.1$32.00
Which should you choose?
Which is better: Claude Haiku 3.5, Mixtral 8x22B Instruct or Mistral Large 2.1?
Claude Haiku 3.5 is the better all-round choice, scoring 46/100 against Mistral Large 2.1 (38) and Mixtral 8x22B Instruct (34). It leads on price, inputs & features and context window. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Claude Haiku 3.5, Mixtral 8x22B Instruct or Mistral Large 2.1?
Claude Haiku 3.5 is cheaper at $0.80 input / $4.00 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); Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $1.60 per million tokens for Claude Haiku 3.5 versus $3.00 for Mixtral 8x22B Instruct (1.9× as much) and $3.00 for Mistral Large 2.1 (1.9× as much).
Which scores higher on benchmarks?
Mistral Large 2.1 scores higher on the Capabilities Index (ECI): Mistral Large 2.1 128.6 (#142 of 165), Claude Haiku 3.5 127.0 (#147 of 165) and Mixtral 8x22B Instruct 122.0 (#155 of 165). The confidence ranges of the top two overlap (124.3–130.7 vs 121.4–129.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Claude Haiku 3.5 38.1%, Mixtral 8x22B Instruct 34.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 3.5, Mixtral 8x22B Instruct and Mistral Large 2.1 yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2.1 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Claude Haiku 3.5 has the largest context window at 200,000 tokens, against 131,072 for Mistral Large 2.1 and 65,536 for Mixtral 8x22B Instruct. Maximum output per response: Claude Haiku 3.5 up to 8,192, Mixtral 8x22B Instruct up to 52,428, Mistral Large 2.1 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 3.5 accepts text, images and PDFs; Mixtral 8x22B Instruct accepts text and PDFs; Mistral Large 2.1 accepts text. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Mixtral 8x22B Instruct and Mistral Large 2.1 publishes its weights and can be self-hosted; Claude Haiku 3.5 is proprietary.
Which is newer?
Mistral Large 2.1 is the newest, released Nov 18, 2024. Claude Haiku 3.5 came out Oct 22, 2024; Mixtral 8x22B Instruct came out Apr 17, 2024. Knowledge cutoff: Claude Haiku 3.5 Jul 31, 2024, Mixtral 8x22B Instruct Jan 31, 2024, Mistral Large 2.1 Nov 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.