Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | — | 47B |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 200k | 32k |
| These models have no shared benchmark scores. | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 50% | — |
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 40.6% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 41.6% | — |
| Overview | ||
| Company | Anthropic | Mistral |
| Release date | Oct 22 2024 | Dec 8 2023 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
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Claude 3.5 Haiku and Mixtral 8×7B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mixtral 8×7B shipped 319 days before Claude 3.5 Haiku, so benchmark comparisons should account for the intervening progress.
Context windows are 200k (Claude 3.5 Haiku) vs 32k (Mixtral 8×7B). Claude 3.5 Haiku is closed, while Mixtral 8×7B is open weight.
Direct benchmark comparisons are unavailable — Claude 3.5 Haiku and Mixtral 8×7B don't publish scores on any of the same benchmarks.