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. | — | 16B |
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 | 4k |
| 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. | 49% | — |
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. | 62.3% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 68% | — |
| Overview | ||
| Company | Anthropic | DeepSeek |
| Release date | Feb 24 2025 | Jan 11 2024 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Claude 3.7 SonnetvsGPT-6.1 SolDeepSeek-MoEvsGPT-6.1 SolClaude 3.7 SonnetvsGemini 4 ArgonDeepSeek-MoEvsGemini 4 ArgonClaude 3.7 SonnetvsMuse Spark OpenDeepSeek-MoEvsMuse Spark OpenClaude 3.7 SonnetvsGrok 4.7DeepSeek-MoEvsGrok 4.7Claude 3.7 SonnetvsMistral Large 4DeepSeek-MoEvsMistral Large 4Claude 3.7 SonnetvsKimi K3DeepSeek-MoEvsKimi K3Frequently asked questions
Claude 3.7 Sonnet and DeepSeek-MoE don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-MoE shipped 410 days before Claude 3.7 Sonnet, so benchmark comparisons should account for the intervening progress.
Context windows are 200k (Claude 3.7 Sonnet) vs 4k (DeepSeek-MoE). Claude 3.7 Sonnet is closed, while DeepSeek-MoE is open weight.
Direct benchmark comparisons are unavailable — Claude 3.7 Sonnet and DeepSeek-MoE don't publish scores on any of the same benchmarks.