Model comparison
Claude Haiku 4.5 vs Mistral 7B
Claude Haiku 4.5 is the stronger model overall, scoring 39.3 to 22.9 on the Noometry Index. Mistral 7B costs 8.0× less per token, which makes it the better buy when Claude Haiku 4.5's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Mistral AISummary
- They share 22 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 8 categories and Mistral 7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Haiku 4.5 leads 43.0 to 7.6.
- The biggest single-benchmark swing is MATH Level 5: 96.4% for Claude Haiku 4.5 and 3.7% for Mistral 7B.
- Mistral 7B is cheaper at $0.25 / $0.25 per million input/output tokens, against $1 / $5 for Claude Haiku 4.5.
- Claude Haiku 4.5 accepts more context: 200K tokens versus 8K.
- Mistral 7B has downloadable open weights; the other is API-only.
Side by side
| Claude Haiku 4.5 | Mistral 7B | |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 39.3 | 22.9 |
| Released | 2025-10-15 | 2023-09-27 |
| Weights | Proprietary | Open |
| Context window | 200K | 8K |
| Max output | 64K | 8K |
| Input $ / M tokens | $1 | $0.25 |
| Output $ / M tokens | $5 | $0.25 |
| Results tracked | 53 | 37 |
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Category by category
Coding Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.9 (#71), Mistral 7B: 25.9 (#321)
| Benchmark | Claude Haiku 4.5 | Mistral 7B |
|---|---|---|
| LMArena Coding | 1454 | 1082 |
| SWE-bench Verified (bash only) | 66.6% | — |
| LMArena WebDev | 1330 | — |
| SWE-bench Multilingual | 64.7% | — |
| SciCode | 43.3% | — |
| WeirdML | 45.4% | — |
| BigCodeBench Instruct | — | 19.5% |
| BigCodeBench Complete | — | 27.3% |
| ALE-Bench | 653.48 | — |
| HumanEval+ | — | 36% |
| MBPP+ | — | 42.1% |
Agentic & Tool Use Not comparable
Claude Haiku 4.5: 33.5 (#50), Mistral 7B: —
| Benchmark | Claude Haiku 4.5 | Mistral 7B |
|---|---|---|
| Terminal-Bench | 35.5% | — |
| Berkeley Function Calling Leaderboard | 68.7% | — |
| DeepResearch Bench | 45.5% | — |
| BALROG | 31.2% | — |
| ExploitBench | 13.7% | — |
| Vending-Bench 2 | 458.89 | — |
Reasoning Claude Haiku 4.5 leads
Claude Haiku 4.5: 15.1 (#310), Mistral 7B: 12.6 (#331)
| Benchmark | Claude Haiku 4.5 | Mistral 7B |
|---|---|---|
| Chess Puzzles | 8% | 0% |
| LMArena Hard Prompts | 1420 | 1067 |
| DTBench | 73.6% | 42.5% |
| Epoch Capabilities Index | 142.42 | 111.97 |
| ARC-AGI-2 | 4% | — |
| NYT Connections (extended) | 14.3% | — |
| ARC-AGI-1 | 47.7% | — |
| CritPt | 0% | — |
| LMCA | 30.9% | — |
| Adversarial NLI | — | 47.1% |
| BIG-Bench Hard | — | 56.1% |
| ForecastBench | 61.4 | — |
| HellaSwag | — | 81% |
| PIQA | — | 83% |
| WinoGrande | — | 75.3% |
Math Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.0 (#69), Mistral 7B: 7.6 (#319)
| Benchmark | Claude Haiku 4.5 | Mistral 7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.7% | 0.3% |
| LMArena Math | 1395 | 1085 |
| MATH Level 5 | 96.4% | 3.7% |
| Omni-MATH | 56.1% | — |
| FrontierMath (Feb 2025 set) | 5.9% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
| GSM8K | — | 54.4% |
Knowledge Claude Haiku 4.5 leads
Claude Haiku 4.5: 37.6 (#146), Mistral 7B: 7.3 (#306)
| Benchmark | Claude Haiku 4.5 | Mistral 7B |
|---|---|---|
| GPQA Diamond | 71.2% | 15.2% |
| LMArena Expert | 1443 | 1036 |
| SimpleQA Verified | 13.2% | — |
| MMLU-Pro | 77.7% | — |
| Vectara Hallucination Rate | 9.8% | — |
| GPQA (HELM) | 60.5% | — |
| ARC (AI2) Challenge | — | 78.6% |
| BoolQ | — | 87.4% |
| MMLU | — | 62.5% |
| OpenBookQA | — | 79.8% |
| TriviaQA | — | 75.2% |
Multimodal Not comparable
Claude Haiku 4.5: 27.0 (#111), Mistral 7B: —
| Benchmark | Claude Haiku 4.5 | Mistral 7B |
|---|---|---|
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1420 | — |
Multilingual Claude Haiku 4.5 leads
Claude Haiku 4.5: 50.1 (#124), Mistral 7B: 26.0 (#278)
| Benchmark | Claude Haiku 4.5 | Mistral 7B |
|---|---|---|
| LMArena Non-English | 1376 | 1012 |
| LMArena Chinese | 1415 | 1009 |
| LMArena French | 1408 | 1036 |
| LMArena German | 1377 | 987 |
| LMArena Japanese | 1339 | 878 |
| LMArena Russian | 1380 | 1018 |
| LMArena Spanish | 1420 | 1026 |
| LMArena Korean | 1346 | — |
Instruction Following Claude Haiku 4.5 leads
Claude Haiku 4.5: 71.6 (#144), Mistral 7B: 54.5 (#275)
| Benchmark | Claude Haiku 4.5 | Mistral 7B |
|---|---|---|
| LMArena Instruction Following | 1414 | 1060 |
| IFEval | 80.1% | — |
Long Context Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.6 (#86), Mistral 7B: 32.2 (#266)
| Benchmark | Claude Haiku 4.5 | Mistral 7B |
|---|---|---|
| LMArena Longer Query | 1427 | 1060 |
Writing & Preference Claude Haiku 4.5 leads
Claude Haiku 4.5: 58.1 (#119), Mistral 7B: 30.9 (#281)
| Benchmark | Claude Haiku 4.5 | Mistral 7B |
|---|---|---|
| LMArena Text | 1396 | 1090 |
| LMArena Creative Writing | 1371 | 1068 |
| LMArena Multi-Turn | 1409 | 1062 |
| WildBench | 83.9% | — |
| EQ-Bench 4 | 1064 | — |
Frequently asked questions
Is Claude Haiku 4.5 better than Mistral 7B?
Claude Haiku 4.5 is the stronger model overall, scoring 39.3 to 22.9 on the Noometry Index. Mistral 7B costs 8.0× less per token, which makes it the better buy when Claude Haiku 4.5's lead doesn't matter for your workload.
Which is cheaper, Claude Haiku 4.5 or Mistral 7B?
Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; Claude Haiku 4.5 lists at $1 and $5.
Is Claude Haiku 4.5 or Mistral 7B better for coding?
Claude Haiku 4.5 scores higher on coding benchmarks: 43.9 versus 25.9 in the Noometry coding category.
Which has the bigger context window?
Claude Haiku 4.5 does, with 200K tokens against 8K.
How many benchmarks do Claude Haiku 4.5 and Mistral 7B share?
22 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and Mistral 7B has 37.