Model comparison
GPT-5.4 Pro vs Llama 3.1-70B
GPT-5.4 Pro is the stronger model overall, scoring 58.8 to 29.4 on the Noometry Index. Llama 3.1-70B costs 169× less per token, which makes it the better buy when GPT-5.4 Pro's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
MetaSummary
- They share 3 benchmarks with published results for both. GPT-5.4 Pro scores higher in 4 categories and Llama 3.1-70B in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.4 Pro leads 72.0 to 12.7.
- The biggest single-benchmark swing is GPQA Diamond: 94.6% for GPT-5.4 Pro and 44.2% for Llama 3.1-70B.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $30 / $180 for GPT-5.4 Pro.
- GPT-5.4 Pro accepts more context: 1.05M tokens versus 128K.
- Llama 3.1-70B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 Pro | Llama 3.1-70B | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 58.8 | 29.4 |
| Released | 2026-03-05 | 2024-07-23 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 128K |
| Max output | 128K | 4K |
| Input $ / M tokens | $30 | $0.40 |
| Output $ / M tokens | $180 | $0.40 |
| Results tracked | 16 | 35 |
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Category by category
Coding GPT-5.4 Pro leads
GPT-5.4 Pro: 42.6 (#89), Llama 3.1-70B: 29.8 (#292)
| Benchmark | GPT-5.4 Pro | Llama 3.1-70B |
|---|---|---|
| WeirdML | 57.4% | 9% |
| BigCodeBench Instruct | — | 46.1% |
| LMArena Coding | — | 1260 |
| BigCodeBench Complete | — | 54.8% |
Agentic & Tool Use Not comparable
GPT-5.4 Pro: —, Llama 3.1-70B: 24.9 (#104)
| Benchmark | GPT-5.4 Pro | Llama 3.1-70B |
|---|---|---|
| TheAgentCompany | — | 6.9% |
| BALROG | — | 27.9% |
Reasoning GPT-5.4 Pro leads
GPT-5.4 Pro: 71.0 (#10), Llama 3.1-70B: 20.8 (#215)
| Benchmark | GPT-5.4 Pro | Llama 3.1-70B |
|---|---|---|
| Epoch Capabilities Index | 159.12 | 125.91 |
| ARC-AGI-2 | 83.3% | — |
| SimpleBench | 74.1% | — |
| ARC-AGI-1 | 94.5% | — |
| CritPt | 30% | — |
| Chess Puzzles | 58.6% | — |
| EnigmaEval | 23.8% | — |
| LMArena Hard Prompts | — | 1241 |
| DTBench | — | 60% |
| LMCA | — | 14.8% |
Math GPT-5.4 Pro leads
GPT-5.4 Pro: 72.0 (#17), Llama 3.1-70B: 12.7 (#298)
| Benchmark | GPT-5.4 Pro | Llama 3.1-70B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 82.5% | — |
| FrontierMath Tier 4 | 58.5% | — |
| OTIS Mock AIME 2024-2025 | — | 3.6% |
| Omni-MATH | — | 21% |
| LMArena Math | — | 1252 |
| MATH Level 5 | — | 36.7% |
| FrontierMath (Feb 2025 set) | 50% | — |
| FrontierMath Tier 4 (v1) | 37.5% | — |
Knowledge GPT-5.4 Pro leads
GPT-5.4 Pro: 68.3 (#6), Llama 3.1-70B: 24.1 (#264)
| Benchmark | GPT-5.4 Pro | Llama 3.1-70B |
|---|---|---|
| GPQA Diamond | 94.6% | 44.2% |
| Humanity's Last Exam | 44.3% | — |
| SimpleQA Verified | 46.3% | — |
| MMLU-Pro | — | 65.3% |
| Vectara Hallucination Rate | 8.3% | — |
| GPQA (HELM) | — | 42.6% |
| LMArena Expert | — | 1209 |
| MMLU | — | 80.1% |
Multilingual Not comparable
GPT-5.4 Pro: —, Llama 3.1-70B: 38.9 (#220)
| Benchmark | GPT-5.4 Pro | Llama 3.1-70B |
|---|---|---|
| LMArena Non-English | — | 1219 |
| LMArena Chinese | — | 1215 |
| LMArena French | — | 1260 |
| LMArena German | — | 1222 |
| LMArena Japanese | — | 1132 |
| LMArena Korean | — | 1140 |
| LMArena Russian | — | 1234 |
| LMArena Spanish | — | 1253 |
Instruction Following Not comparable
GPT-5.4 Pro: —, Llama 3.1-70B: 65.5 (#218)
| Benchmark | GPT-5.4 Pro | Llama 3.1-70B |
|---|---|---|
| IFEval | — | 82.1% |
| LMArena Instruction Following | — | 1231 |
Long Context Not comparable
GPT-5.4 Pro: —, Llama 3.1-70B: 37.6 (#208)
| Benchmark | GPT-5.4 Pro | Llama 3.1-70B |
|---|---|---|
| LMArena Longer Query | — | 1241 |
Writing & Preference Not comparable
GPT-5.4 Pro: —, Llama 3.1-70B: 35.6 (#262)
| Benchmark | GPT-5.4 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-5.4 Pro better than Llama 3.1-70B?
GPT-5.4 Pro is the stronger model overall, scoring 58.8 to 29.4 on the Noometry Index. Llama 3.1-70B costs 169× less per token, which makes it the better buy when GPT-5.4 Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5.4 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-5.4 Pro lists at $30 and $180.
Is GPT-5.4 Pro or Llama 3.1-70B better for coding?
GPT-5.4 Pro scores higher on coding benchmarks: 42.6 versus 29.8 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 Pro does, with 1.05M tokens against 128K.
How many benchmarks do GPT-5.4 Pro and Llama 3.1-70B share?
3 benchmarks have published results for both models. GPT-5.4 Pro has 16 scored results on Noometry and Llama 3.1-70B has 35.