Model comparison
GPT-5.6 Terra vs Llama 3-8B
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 25.5 on the Noometry Index.
Last verified . 22 shared benchmarks.
MetaSummary
- They share 22 benchmarks with published results for both. GPT-5.6 Terra scores higher in 8 categories and Llama 3-8B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Terra leads 81.6 to 8.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 99.7% for GPT-5.6 Terra and 1.9% for Llama 3-8B.
- Llama 3-8B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.6 Terra | Llama 3-8B | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 59.2 | 25.5 |
| Released | 2026-07-09 | 2024-04-18 |
| Weights | Proprietary | Open |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $2 | — |
| Output $ / M tokens | $12 | — |
| Results tracked | 52 | 34 |
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Category by category
Coding GPT-5.6 Terra leads
GPT-5.6 Terra: 57.7 (#19), Llama 3-8B: 31.0 (#289)
| Benchmark | GPT-5.6 Terra | Llama 3-8B |
|---|---|---|
| LMArena Coding | 1484 | 1152 |
| DeepSWE | 69.6% | — |
| FrontierCode | 41.3% | — |
| CursorBench | 41.3% | — |
| LMArena WebDev | 1522 | — |
| SciCode | 55% | — |
| WeirdML | 78.3% | — |
| BigCodeBench Instruct | — | 31.9% |
| BigCodeBench Complete | — | 36.9% |
| ALE-Bench | 1,951 | — |
| HumanEval+ | — | 56.7% |
| MBPP+ | — | 54.8% |
Agentic & Tool Use Not comparable
GPT-5.6 Terra: 40.1 (#25), Llama 3-8B: —
| Benchmark | GPT-5.6 Terra | Llama 3-8B |
|---|---|---|
| APEX-Agents | 58.2% | — |
| BALROG | 53.2% | — |
| GDP.pdf | 24.7% | — |
| Vending-Bench 2 | 7,343 | — |
Reasoning GPT-5.6 Terra leads
GPT-5.6 Terra: 60.7 (#21), Llama 3-8B: 14.3 (#326)
| Benchmark | GPT-5.6 Terra | Llama 3-8B |
|---|---|---|
| Chess Puzzles | 54% | 0% |
| LMArena Hard Prompts | 1468 | 1133 |
| DTBench | 93.3% | 43.9% |
| Epoch Capabilities Index | 159.62 | 116.45 |
| ARC-AGI-2 | 83.9% | — |
| SimpleBench | 48.9% | — |
| Kagi LLM Benchmark | 51.3% | — |
| NYT Connections (extended) | 78.4% | — |
| ARC-AGI-1 | 96.5% | — |
| CritPt | 30% | — |
| Mystery Game Puzzles | 35% | — |
| LMCA | 55% | — |
| Surface Evolver Bench | 83.8% | — |
| Adversarial NLI | — | 57.3% |
| ForecastBench | — | 58.6 |
| WinoGrande | — | 75.7% |
Math GPT-5.6 Terra leads
GPT-5.6 Terra: 81.6 (#12), Llama 3-8B: 8.8 (#323)
| Benchmark | GPT-5.6 Terra | Llama 3-8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 99.7% | 1.9% |
| LMArena Math | 1466 | 1151 |
| FrontierMath (Tiers 1-3) | 86% | — |
| FrontierMath Tier 4 | 70.7% | — |
| ProofBench | 74% | — |
| MATH Level 5 | — | 6.1% |
Knowledge GPT-5.6 Terra leads
GPT-5.6 Terra: 61.2 (#30), Llama 3-8B: 7.8 (#308)
| Benchmark | GPT-5.6 Terra | Llama 3-8B |
|---|---|---|
| GPQA Diamond | 93.3% | 26.1% |
| LMArena Expert | 1492 | 1113 |
| SimpleQA Verified | 43.2% | — |
| ARC (AI2) Challenge | — | 82.8% |
| MMLU | — | 68.8% |
| OpenBookQA | — | 82.6% |
| TriviaQA | — | 67.7% |
Multimodal Not comparable
GPT-5.6 Terra: 47.3 (#11), Llama 3-8B: —
| Benchmark | GPT-5.6 Terra | Llama 3-8B |
|---|---|---|
| LMArena Vision | 1271 | — |
| Blueprint-Bench 2 | 30.8% | — |
| Furniture Assembly | 54.2% | — |
| LMArena Document | 1472 | — |
Multilingual GPT-5.6 Terra leads
GPT-5.6 Terra: 54.4 (#44), Llama 3-8B: 30.8 (#261)
| Benchmark | GPT-5.6 Terra | Llama 3-8B |
|---|---|---|
| LMArena Non-English | 1439 | 1098 |
| LMArena Chinese | 1513 | 1076 |
| LMArena French | 1471 | 1159 |
| LMArena German | 1460 | 1104 |
| LMArena Japanese | 1457 | 967 |
| LMArena Korean | 1425 | 1004 |
| LMArena Russian | 1450 | 1109 |
| LMArena Spanish | 1448 | 1173 |
Instruction Following GPT-5.6 Terra leads
GPT-5.6 Terra: 76.4 (#40), Llama 3-8B: 58.4 (#260)
| Benchmark | GPT-5.6 Terra | Llama 3-8B |
|---|---|---|
| LMArena Instruction Following | 1454 | 1127 |
Long Context GPT-5.6 Terra leads
GPT-5.6 Terra: 44.4 (#68), Llama 3-8B: 34.2 (#251)
| Benchmark | GPT-5.6 Terra | Llama 3-8B |
|---|---|---|
| LMArena Longer Query | 1451 | 1128 |
Writing & Preference GPT-5.6 Terra leads
GPT-5.6 Terra: 70.2 (#23), Llama 3-8B: 37.5 (#256)
| Benchmark | GPT-5.6 Terra | Llama 3-8B |
|---|---|---|
| LMArena Text | 1447 | 1166 |
| LMArena Creative Writing | 1410 | 1150 |
| LMArena Multi-Turn | 1449 | 1152 |
| EQ-Bench Creative Writing | 1855 | — |
| EQ-Bench 4 | 1234 | — |
Frequently asked questions
Is GPT-5.6 Terra better than Llama 3-8B?
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 25.5 on the Noometry Index.
Is GPT-5.6 Terra or Llama 3-8B better for coding?
GPT-5.6 Terra scores higher on coding benchmarks: 57.7 versus 31.0 in the Noometry coding category.
How many benchmarks do GPT-5.6 Terra and Llama 3-8B share?
22 benchmarks have published results for both models. GPT-5.6 Terra has 52 scored results on Noometry and Llama 3-8B has 34.