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. | — | 7B/67B |
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. | 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 | DeepSeek |
| Release date | Oct 22 2024 | Nov 29 2023 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Claude 3.5 HaikuvsGPT-6.1 SolDeepSeek-LLMvsGPT-6.1 SolClaude 3.5 HaikuvsGemini 4 ArgonDeepSeek-LLMvsGemini 4 ArgonClaude 3.5 HaikuvsMuse Spark OpenDeepSeek-LLMvsMuse Spark OpenClaude 3.5 HaikuvsGrok 4.7DeepSeek-LLMvsGrok 4.7Claude 3.5 HaikuvsMistral Large 4DeepSeek-LLMvsMistral Large 4Claude 3.5 HaikuvsKimi K3DeepSeek-LLMvsKimi K3Frequently asked questions
Claude 3.5 Haiku and DeepSeek-LLM don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-LLM shipped 328 days before Claude 3.5 Haiku, so benchmark comparisons should account for the intervening progress.
Context windows are 200k (Claude 3.5 Haiku) vs 4k (DeepSeek-LLM). Claude 3.5 Haiku is closed, while DeepSeek-LLM is open weight.
Direct benchmark comparisons are unavailable — Claude 3.5 Haiku and DeepSeek-LLM don't publish scores on any of the same benchmarks.