Deepseek Llm 67B Chat — Benchmarks
Benchmark scores for Deepseek Llm 67B Chat aggregated from public leaderboards (4 boards), with how it ranks among open models and how it compares with its nearest neighbours. See hardware requirements for what you need to run it.
No llmrun Composite Score for Deepseek Llm 67B Chat: the score is only published for a model measured on at least 4 of the boards in the score panel, spanning at least 2 benchmark categories and including a reasoning or coding board — or on 3 boards that narrow its score to a 90% range of at most 15.6 points. Either way the results must come from at least two different benchmarks. Its individual scores below stand on their own — see how the llmrun Composite Score gets calculated.
Deepseek Llm 67B Chat reasoning benchmarks
Multi-step logic and problem-solving — can the model think through a hard problem rather than recall an answer.
24.6%
24.6%
median 54.0%open leader 93.1%
Overall best: Gemini 4 Argon (high) 96.4%
8th percentile · #90 of 98 open · #291 of 300 all
IndependentEpoch AI ·
Deepseek Llm 67B Chat math benchmarks
Symbolic and quantitative problem-solving, from competition math to multi-step calculation.
0.8%
0.8%
median 52.8%open leader 98.6%
Overall best: Claude Fable 5 (high) 100.0%
6th percentile · #80 of 86 open · #276 of 283 all
IndependentEpoch AI ·
6.4%
6.4%
median 41.6%open leader 96.6%
Overall best: GPT 5 (Aug 07, 2025, high) 98.1%
11th percentile · #35 of 39 open · #102 of 107 all
IndependentEpoch AI ·
Deepseek Llm 67B Chat instruction following benchmarks
How precisely a model obeys explicit, verifiable instructions — format, length, and content constraints — and, more broadly, how much people prefer its responses head-to-head in blind human voting.
1185.1
1185.1
median 1321.5open leader 1487.1
Overall best: Gemini 4 Argon (High) 1523.9
20th percentile · #150 of 187 open · #343 of 405 all
ArenaArena ·
Scores aggregated from public benchmark sources (Epoch AI: 3 boards, Arena: 1 board) — each linked from the benchmark pages. llmrun does not run these benchmarks. Percentiles and ranks are among open models in the llmrun catalogue; the median and leader marks refer to the same field.