Model comparison
DeepSeek-R1-Distill-Llama-70B vs Grok-2 (Dec 2024)
DeepSeek-R1-Distill-Llama-70B is the stronger model overall, scoring 37.8 to 33.7 on the Noometry Index.
Last verified . 10 shared benchmarks.
DeepSeekSummary
- They share 10 benchmarks with published results for both. DeepSeek-R1-Distill-Llama-70B scores higher in 6 categories and Grok-2 (Dec 2024) in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek-R1-Distill-Llama-70B leads 36.0 to 20.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 51.4% for DeepSeek-R1-Distill-Llama-70B and 11.5% for Grok-2 (Dec 2024).
- DeepSeek-R1-Distill-Llama-70B has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-R1-Distill-Llama-70B | Grok-2 (Dec 2024) | |
|---|---|---|
| Provider | DeepSeek | xAI |
| Noometry Index | 37.8 | 33.7 |
| Released | 2025-01-20 | 2024-08-13 |
| Weights | Open | Proprietary |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 13 | 34 |
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Category by category
Coding DeepSeek-R1-Distill-Llama-70B leads
DeepSeek-R1-Distill-Llama-70B: 36.8 (#202), Grok-2 (Dec 2024): 33.3 (#258)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Grok-2 (Dec 2024) |
|---|---|---|
| LiveBench Coding | 51.6% | 46.4% |
| WeirdML | — | 22.2% |
| BigCodeBench Instruct | 35.3% | — |
| LMArena Coding | — | 1287 |
| BigCodeBench Complete | 49.9% | — |
Reasoning DeepSeek-R1-Distill-Llama-70B leads
DeepSeek-R1-Distill-Llama-70B: 24.9 (#156), Grok-2 (Dec 2024): 16.9 (#299)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Grok-2 (Dec 2024) |
|---|---|---|
| LiveBench Reasoning | 67.6% | 54.8% |
| LiveBench Data Analysis | 55.9% | 54.5% |
| LiveBench | 54.5% | 54.3% |
| SimpleBench | — | 22.7% |
| Kagi LLM Benchmark | 52.3% | — |
| LMArena Hard Prompts | — | 1272 |
| DTBench | — | 65.2% |
| Epoch Capabilities Index | — | 130.48 |
Math DeepSeek-R1-Distill-Llama-70B leads
DeepSeek-R1-Distill-Llama-70B: 36.0 (#176), Grok-2 (Dec 2024): 20.8 (#284)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Grok-2 (Dec 2024) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 51.4% | 11.5% |
| LiveBench Math | 58.1% | 54.9% |
| MATH Level 5 | 89.9% | 63.5% |
| LMArena Math | — | 1283 |
| FrontierMath (Feb 2025 set) | — | 0.7% |
Knowledge Too close to call
DeepSeek-R1-Distill-Llama-70B: 30.7 (#225), Grok-2 (Dec 2024): 29.8 (#233)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Grok-2 (Dec 2024) |
|---|---|---|
| GPQA Diamond | 55.7% | 53.8% |
| Confabulations | — | 20.1% |
| LMArena Expert | — | 1254 |
Multilingual Not comparable
DeepSeek-R1-Distill-Llama-70B: —, Grok-2 (Dec 2024): 43.1 (#188)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Non-English | — | 1282 |
| LMArena Chinese | — | 1289 |
| LMArena French | — | 1318 |
| LMArena German | — | 1287 |
| LMArena Japanese | — | 1244 |
| LMArena Korean | — | 1237 |
| LMArena Russian | — | 1286 |
| LMArena Spanish | — | 1281 |
Instruction Following DeepSeek-R1-Distill-Llama-70B leads
DeepSeek-R1-Distill-Llama-70B: 68.2 (#190), Grok-2 (Dec 2024): 66.9 (#202)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Grok-2 (Dec 2024) |
|---|---|---|
| LiveBench Instruction Following | 69.9% | 69.6% |
| LMArena Instruction Following | — | 1270 |
Long Context Not comparable
DeepSeek-R1-Distill-Llama-70B: —, Grok-2 (Dec 2024): 38.8 (#190)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Grok-2 (Dec 2024) |
|---|---|---|
| LMArena Longer Query | — | 1276 |
Writing & Preference Too close to call
DeepSeek-R1-Distill-Llama-70B: 49.0 (#194), Grok-2 (Dec 2024): 48.6 (#198)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Grok-2 (Dec 2024) |
|---|---|---|
| LiveBench Language | 23.8% | 45.6% |
| LMArena Text | — | 1305 |
| LMArena Creative Writing | — | 1284 |
| Short-Story Creative Writing | — | 63.6% |
| LMArena Multi-Turn | — | 1290 |
Frequently asked questions
Is DeepSeek-R1-Distill-Llama-70B better than Grok-2 (Dec 2024)?
DeepSeek-R1-Distill-Llama-70B is the stronger model overall, scoring 37.8 to 33.7 on the Noometry Index.
Is DeepSeek-R1-Distill-Llama-70B or Grok-2 (Dec 2024) better for coding?
DeepSeek-R1-Distill-Llama-70B scores higher on coding benchmarks: 36.8 versus 33.3 in the Noometry coding category.
How many benchmarks do DeepSeek-R1-Distill-Llama-70B and Grok-2 (Dec 2024) share?
10 benchmarks have published results for both models. DeepSeek-R1-Distill-Llama-70B has 13 scored results on Noometry and Grok-2 (Dec 2024) has 34.