Model comparison
GPT-5.2 Pro vs Llama 3.1-70B
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 29.6 on the Noometry Index. Llama 3.1-70B costs 144× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
MetaSummary
- They share 1 benchmark with published results for both. GPT-5.2 Pro scores higher in 2 categories and Llama 3.1-70B in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.2 Pro leads 65.3 to 13.5.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $21 / $168 for GPT-5.2 Pro.
- GPT-5.2 Pro accepts more context: 400K tokens versus 128K.
- Llama 3.1-70B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.2 Pro | Llama 3.1-70B | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 52.3 | 29.6 |
| Released | 2025-12-11 | 2024-07-23 |
| Weights | Proprietary | Open |
| Context window | 400K | 128K |
| Max output | 128K | 4K |
| Input $ / M tokens | $21 | $0.40 |
| Output $ / M tokens | $168 | $0.40 |
| Results tracked | 8 | 35 |
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Category by category
Coding Not comparable
GPT-5.2 Pro: —, Llama 3.1-70B: 30.3 (#296)
| Benchmark | GPT-5.2 Pro | Llama 3.1-70B |
|---|---|---|
| WeirdML | — | 9% |
| BigCodeBench Instruct | — | 46.1% |
| LMArena Coding | — | 1260 |
| BigCodeBench Complete | — | 54.8% |
Agentic & Tool Use Not comparable
GPT-5.2 Pro: —, Llama 3.1-70B: 25.1 (#112)
| Benchmark | GPT-5.2 Pro | Llama 3.1-70B |
|---|---|---|
| TheAgentCompany | — | 6.9% |
| BALROG | — | 27.9% |
Reasoning GPT-5.2 Pro leads
GPT-5.2 Pro: 51.5 (#33), Llama 3.1-70B: 21.6 (#220)
| Benchmark | GPT-5.2 Pro | Llama 3.1-70B |
|---|---|---|
| Epoch Capabilities Index | 155.4 | 125.92 |
| ARC-AGI-2 | 54.2% | — |
| SimpleBench | 57.4% | — |
| NYT Connections (extended) | 79.3% | — |
| ARC-AGI-1 | 90.5% | — |
| LMArena Hard Prompts | — | 1241 |
| DTBench | — | 60% |
| LMCA | — | 14.8% |
Math GPT-5.2 Pro leads
GPT-5.2 Pro: 65.3 (#29), Llama 3.1-70B: 13.5 (#304)
| Benchmark | GPT-5.2 Pro | Llama 3.1-70B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 74% | — |
| FrontierMath Tier 4 | 46% | — |
| OTIS Mock AIME 2024-2025 | — | 3.6% |
| Omni-MATH | — | 21% |
| LMArena Math | — | 1252 |
| MATH Level 5 | — | 36.7% |
| FrontierMath Tier 4 (v1) | 31.3% | — |
Knowledge Not comparable
GPT-5.2 Pro: —, Llama 3.1-70B: 24.2 (#269)
| Benchmark | GPT-5.2 Pro | Llama 3.1-70B |
|---|---|---|
| GPQA Diamond | — | 44.2% |
| MMLU-Pro | — | 65.3% |
| GPQA (HELM) | — | 42.6% |
| LMArena Expert | — | 1209 |
| MMLU | — | 80.1% |
Multilingual Not comparable
GPT-5.2 Pro: —, Llama 3.1-70B: 38.8 (#225)
| Benchmark | GPT-5.2 Pro | Llama 3.1-70B |
|---|---|---|
| LMArena Non-English | — | 1219 |
| LMArena Chinese | — | 1215 |
| LMArena French | — | 1261 |
| LMArena German | — | 1222 |
| LMArena Japanese | — | 1132 |
| LMArena Korean | — | 1140 |
| LMArena Russian | — | 1234 |
| LMArena Spanish | — | 1253 |
Instruction Following Not comparable
GPT-5.2 Pro: —, Llama 3.1-70B: 65.3 (#223)
| Benchmark | GPT-5.2 Pro | Llama 3.1-70B |
|---|---|---|
| IFEval | — | 82.1% |
| LMArena Instruction Following | — | 1231 |
Long Context Not comparable
GPT-5.2 Pro: —, Llama 3.1-70B: 37.6 (#214)
| Benchmark | GPT-5.2 Pro | Llama 3.1-70B |
|---|---|---|
| LMArena Longer Query | — | 1241 |
Writing & Preference Not comparable
GPT-5.2 Pro: —, Llama 3.1-70B: 35.4 (#267)
| Benchmark | GPT-5.2 Pro | Llama 3.1-70B |
|---|---|---|
| LMArena Text | — | 1261 |
| LMArena Creative Writing | — | 1232 |
| EQ-Bench Creative Writing | — | 784 |
| WildBench | — | 75.8% |
| LMArena Multi-Turn | — | 1256 |
Frequently asked questions
Is GPT-5.2 Pro better than Llama 3.1-70B?
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 29.6 on the Noometry Index. Llama 3.1-70B costs 144× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5.2 Pro or Llama 3.1-70B?
Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; GPT-5.2 Pro lists at $21 and $168.
Which has the bigger context window?
GPT-5.2 Pro does, with 400K tokens against 128K.
How many benchmarks do GPT-5.2 Pro and Llama 3.1-70B share?
1 benchmark has published results for both models. GPT-5.2 Pro has 8 scored results on Noometry and Llama 3.1-70B has 35.