Model comparison
Llama2 70b Steerlm Chat vs o3
o3 is the stronger model overall, scoring 47.5 to 31.8 on the Noometry Index.
Last verified . 9 shared benchmarks.
NVIDIASummary
- They share 9 benchmarks with published results for both. Llama2 70b Steerlm Chat scores higher in 0 categories and o3 in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where o3 leads 63.5 to 31.6.
- Llama2 70b Steerlm Chat has downloadable open weights; the other is API-only.
Side by side
| Llama2 70b Steerlm Chat | o3 | |
|---|---|---|
| Provider | NVIDIA | OpenAI |
| Noometry Index | 31.8 | 47.5 |
| Released | — | 2025-04-16 |
| Weights | Open | Proprietary |
| Context window | — | 200K |
| Max output | — | 100K |
| Input $ / M tokens | — | $2 |
| Output $ / M tokens | — | $8 |
| Results tracked | 9 | 63 |
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Category by category
Coding o3 leads
Llama2 70b Steerlm Chat: 29.9 (#300), o3: 46.8 (#64)
| Benchmark | Llama2 70b Steerlm Chat | o3 |
|---|---|---|
| LMArena Coding | 1025 | 1408 |
| SWE-bench Verified | — | 62.3% |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| GSO | — | 8.8% |
| WeirdML | — | 52.4% |
| CadEval | — | 74% |
| ALE-Bench | — | 933.55 |
Agentic & Tool Use Not comparable
Llama2 70b Steerlm Chat: —, o3: 34.5 (#44)
| Benchmark | Llama2 70b Steerlm Chat | o3 |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 63% |
| GDPval | — | 30.8% |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |
Reasoning o3 leads
Llama2 70b Steerlm Chat: 20.0 (#246), o3: 32.0 (#78)
| Benchmark | Llama2 70b Steerlm Chat | o3 |
|---|---|---|
| LMArena Hard Prompts | 1047 | 1402 |
| ARC-AGI-2 | — | 6.5% |
| SimpleBench | — | 53.1% |
| Kagi LLM Benchmark | — | 67.6% |
| ARC-AGI-1 | — | 60.8% |
| CritPt | — | 1.4% |
| Chess Puzzles | — | 38% |
| EnigmaEval | — | 13.1% |
| Mystery Game Puzzles | — | 29% |
| DTBench | — | 84.8% |
| LMCA | — | 39.7% |
| Epoch Capabilities Index | — | 146.86 |
| ForecastBench | — | 62.5 |
Math o3 leads
Llama2 70b Steerlm Chat: 31.3 (#226), o3: 50.2 (#58)
| Benchmark | Llama2 70b Steerlm Chat | o3 |
|---|---|---|
| LMArena Math | 1072 | 1426 |
| FrontierMath (Tiers 1-3) | — | 33.3% |
| OTIS Mock AIME 2024-2025 | — | 84.4% |
| Omni-MATH | — | 71.4% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 18.7% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Not comparable
Llama2 70b Steerlm Chat: —, o3: 54.6 (#52)
| Benchmark | Llama2 70b Steerlm Chat | o3 |
|---|---|---|
| GPQA Diamond | — | 81.8% |
| Humanity's Last Exam | — | 20.3% |
| SimpleQA Verified | — | 49.4% |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| GPQA (HELM) | — | 75.3% |
| LMArena Expert | — | 1402 |
Multimodal Not comparable
Llama2 70b Steerlm Chat: —, o3: 41.4 (#36)
| Benchmark | Llama2 70b Steerlm Chat | o3 |
|---|---|---|
| LMArena Vision | — | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |
Multilingual o3 leads
Llama2 70b Steerlm Chat: 28.8 (#270), o3: 51.7 (#105)
| Benchmark | Llama2 70b Steerlm Chat | o3 |
|---|---|---|
| LMArena Non-English | 1063 | 1401 |
| LMArena Chinese | — | 1437 |
| LMArena French | — | 1430 |
| LMArena German | — | 1420 |
| LMArena Japanese | — | 1403 |
| LMArena Korean | — | 1370 |
| LMArena Russian | — | 1406 |
| LMArena Spanish | — | 1395 |
Instruction Following o3 leads
Llama2 70b Steerlm Chat: 54.2 (#279), o3: 72.8 (#127)
| Benchmark | Llama2 70b Steerlm Chat | o3 |
|---|---|---|
| LMArena Instruction Following | 1060 | 1368 |
| IFEval | — | 86.9% |
Long Context o3 leads
Llama2 70b Steerlm Chat: 30.4 (#288), o3: 53.3 (#6)
| Benchmark | Llama2 70b Steerlm Chat | o3 |
|---|---|---|
| LMArena Longer Query | 998 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |
Writing & Preference o3 leads
Llama2 70b Steerlm Chat: 31.6 (#283), o3: 63.5 (#64)
| Benchmark | Llama2 70b Steerlm Chat | o3 |
|---|---|---|
| LMArena Text | 1098 | 1410 |
| LMArena Creative Writing | 1091 | 1359 |
| LMArena Multi-Turn | 1058 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| EQ-Bench Creative Writing | — | 1676 |
| WildBench | — | 86.1% |
Frequently asked questions
Is Llama2 70b Steerlm Chat better than o3?
o3 is the stronger model overall, scoring 47.5 to 31.8 on the Noometry Index.
Is Llama2 70b Steerlm Chat or o3 better for coding?
o3 scores higher on coding benchmarks: 46.8 versus 29.9 in the Noometry coding category.
How many benchmarks do Llama2 70b Steerlm Chat and o3 share?
9 benchmarks have published results for both models. Llama2 70b Steerlm Chat has 9 scored results on Noometry and o3 has 63.