Meta · Open weightsLlama 3.1 Nemotron Instruct 70B
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Llama 3.1 Nemotron Instruct 70B
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Meta · Released 2024-10-15 · v2024-10-15 · Open
ACTIVETextCodeReasoning
Language Cap
21
Cadle Language Cap 21 · 59%
Benchmark average
41.5
Not enough benchmark results yet
Pricing
Unlisted
no list price
CADLE CAP vs MODEL MATRIX
Cadle Cap ranks models on every published score we have for them — harder benchmarks weigh more. Missing tests are skipped, not zeroed. It answers who is stronger than whom in today's pool.
Model Matrix is the datasheet: Overall, Intelligence, Coding, Agentic, MMLU, GPQA, Math, LiveCodeBench, HumanEval, Reason, ARC-AGI. A dash means unmeasured. AVG is an importance-weighted mean of that model's filled cells only.
MODEL MATRIX · TRUTH CENTER CELLS
Overall
No data yet
Intelligence
6.9
Coding
No data yet
Agentic
23.1
MMLU
69.0
GPQA
46.5
Math
73.3
LiveCodeBench
16.9
HumanEval
No data yet
Reason
30.8
ARC-AGI
No data yet
Coverage AVG
41.5
Cadle Cap ranks models with within-benchmark percentiles so ARC-AGI ~40 and MMLU ~90 never compete raw. Coverage AVG is an importance-weighted mean of filled expert cells only — blanks are skipped, not zeroed.
ANALYSIS · TRUTH CENTER
Hard benches (GPQA · ARC-AGI · LCB · Agentic) sit left — a mid-40 on ARC-AGI can still be frontier. Broader benches on the right are easier and often higher.