# DeepSeek LLM 67B vs DeepSeek-R1

> DeepSeek-R1 is the stronger model overall, scoring 42.3 to 24.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-llm-67b-vs-deepseek-r1
- Last updated: 2026-10-10
- Shared benchmarks: 14

## Summary

- They share 14 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and DeepSeek-R1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-R1 leads 44.5 to 7.0.
- The biggest single-benchmark swing is MATH Level 5: 6.4% for DeepSeek LLM 67B and 96.6% for DeepSeek-R1.
- DeepSeek LLM 67B has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek LLM 67B | DeepSeek-R1 |
|---|---|---|
| Provider | DeepSeek | DeepSeek |
| Noometry Index | 24.9 | 42.3 |
| Rank | 347 | 115 |
| Context | — | 164K |
| Input $/M | — | $0.50 |
| Output $/M | — | $2.15 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek LLM 67B: 31.9 (#278)
- DeepSeek-R1: 46.3 (#68)

| Benchmark | DeepSeek LLM 67B | DeepSeek-R1 |
|---|---|---|
| LMArena Coding | 1096 | 1427 |
| Aider Polyglot | — | 71.4% |
| SciCode | — | 35.7% |
| WeirdML | — | 41.6% |
| LiveBench Coding | — | 66.7% |
| ALE-Bench | — | 804.12 |
| AlgoTune | — | 1.7 |

## Agentic & Tool Use

- DeepSeek LLM 67B: —
- DeepSeek-R1: 30.7 (#75)

| Benchmark | DeepSeek LLM 67B | DeepSeek-R1 |
|---|---|---|
| DeepResearch Bench | — | 35.1% |
| BALROG | — | 34.9% |
| METR Time Horizons | — | 53.8% |

## Reasoning

- DeepSeek LLM 67B: 16.5 (#304)
- DeepSeek-R1: 18.6 (#278)

| Benchmark | DeepSeek LLM 67B | DeepSeek-R1 |
|---|---|---|
| LMArena Hard Prompts | 1070 | 1416 |
| Epoch Capabilities Index | 110.5 | 141.29 |
| ARC-AGI-2 | — | 1.3% |
| SimpleBench | — | 40.8% |
| Kagi LLM Benchmark | — | 69.4% |
| ARC-AGI-1 | — | 21.2% |
| CritPt | — | 1.1% |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | — | 83.2% |
| LiveBench Data Analysis | — | 69.8% |
| ForecastBench | — | 60 |
| LiveBench | — | 71.6% |

## Math

- DeepSeek LLM 67B: 8.7 (#324)
- DeepSeek-R1: 43.8 (#79)

| Benchmark | DeepSeek LLM 67B | DeepSeek-R1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.8% | 66.4% |
| LMArena Math | 1108 | 1400 |
| MATH Level 5 | 6.4% | 96.6% |
| Omni-MATH | — | 42.4% |
| LiveBench Math | — | 80.7% |

## Knowledge

- DeepSeek LLM 67B: 7.0 (#313)
- DeepSeek-R1: 44.5 (#87)

| Benchmark | DeepSeek LLM 67B | DeepSeek-R1 |
|---|---|---|
| GPQA Diamond | 24.6% | 76.3% |
| MMLU-Pro | — | 79.3% |
| Confabulations | — | 12.7% |
| Vectara Hallucination Rate | — | 11.3% |
| GPQA (HELM) | — | 66.6% |
| LMArena Expert | — | 1394 |

## Multilingual

- DeepSeek LLM 67B: 29.4 (#267)
- DeepSeek-R1: 52.4 (#85)

| Benchmark | DeepSeek LLM 67B | DeepSeek-R1 |
|---|---|---|
| LMArena Non-English | 1073 | 1412 |
| LMArena Chinese | 1132 | 1442 |
| LMArena French | — | 1417 |
| LMArena German | — | 1404 |
| LMArena Japanese | — | 1391 |
| LMArena Korean | — | 1360 |
| LMArena Russian | — | 1423 |
| LMArena Spanish | — | 1411 |

## Instruction Following

- DeepSeek LLM 67B: 55.4 (#277)
- DeepSeek-R1: 72.0 (#143)

| Benchmark | DeepSeek LLM 67B | DeepSeek-R1 |
|---|---|---|
| LMArena Instruction Following | 1079 | 1382 |
| LiveBench Instruction Following | — | 80.5% |
| IFEval | — | 78.4% |

## Long Context

- DeepSeek LLM 67B: 33.1 (#265)
- DeepSeek-R1: 45.4 (#36)

| Benchmark | DeepSeek LLM 67B | DeepSeek-R1 |
|---|---|---|
| LMArena Longer Query | 1092 | 1391 |
| Fiction.LiveBench | — | 75% |

## Writing & Preference

- DeepSeek LLM 67B: 31.6 (#282)
- DeepSeek-R1: 61.4 (#88)

| Benchmark | DeepSeek LLM 67B | DeepSeek-R1 |
|---|---|---|
| LMArena Text | 1105 | 1428 |
| LMArena Creative Writing | 1067 | 1405 |
| LMArena Multi-Turn | 1082 | 1405 |
| Short-Story Creative Writing | — | 83% |
| EQ-Bench Creative Writing | — | 1500 |
| WildBench | — | 82.8% |
| LiveBench Language | — | 48.5% |

## FAQ

### Is DeepSeek LLM 67B better than DeepSeek-R1?

DeepSeek-R1 is the stronger model overall, scoring 42.3 to 24.9 on the Noometry Index.

### Is DeepSeek LLM 67B or DeepSeek-R1 better for coding?

DeepSeek-R1 scores higher on coding benchmarks: 46.3 versus 31.9 in the Noometry coding category.

### How many benchmarks do DeepSeek LLM 67B and DeepSeek-R1 share?

14 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and DeepSeek-R1 has 52.