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. | 70B | 4B |
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. | 16k | 256k |
| These models have no shared benchmark scores. | ||
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. | — | 59.5% |
HumanEvalFunction synthesis — 164 small Python problems: the AI is given a function's description and has to write the working function. This was the coding benchmark of the GPT-3.5 and GPT-4 era, before the field moved to fixing real bugs in real repositories. Higher is better. | 53% | — |
Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | — | 18.1% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 72.41% |
IFBenchInstruction following — Tests whether the AI can follow detailed instructions and satisfy multiple constraints at once. Higher is better. | — | 77.94% |
| Overview | ||
| Company | Meta | NVIDIA |
| Release date | Jan 29 2024 | Oct 16 2026 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Code Llama 70BvsClaude Fable 5.2Nemotron Labs Dory 1.0 4BvsClaude Fable 5.2Code Llama 70BvsGPT-6.1 TerraNemotron Labs Dory 1.0 4BvsGPT-6.1 TerraCode Llama 70BvsGemini 4 CarbonNemotron Labs Dory 1.0 4BvsGemini 4 CarbonCode Llama 70BvsGrok 4.7Nemotron Labs Dory 1.0 4BvsGrok 4.7Code Llama 70BvsDeepSeek-V4.1-Flash-1017Nemotron Labs Dory 1.0 4BvsDeepSeek-V4.1-Flash-1017Code Llama 70BvsMistral Large 4Nemotron Labs Dory 1.0 4BvsMistral Large 4Frequently asked questions
Code Llama 70B and Nemotron Labs Dory 1.0 4B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama 70B shipped 991 days before Nemotron Labs Dory 1.0 4B, so benchmark comparisons should account for the intervening progress.
Code Llama 70B has 70B parameters, while Nemotron Labs Dory 1.0 4B has 4B. Context windows are 16k (Code Llama 70B) vs 256k (Nemotron Labs Dory 1.0 4B).
Direct benchmark comparisons are unavailable — Code Llama 70B and Nemotron Labs Dory 1.0 4B don't publish scores on any of the same benchmarks.