Model comparison
GPT-5.6 Terra vs Olmo 7b Instruct
GPT-5.6 Terra is the stronger model overall, scoring 59.1 to 29.7 on the Noometry Index.
Last verified . 10 shared benchmarks.
Allen Institute for AI (Ai2)Summary
- They share 10 benchmarks with published results for both. GPT-5.6 Terra scores higher in 6 categories and Olmo 7b Instruct in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Terra leads 81.5 to 27.8.
- Olmo 7b Instruct has downloadable open weights; the other is API-only.
Side by side
| GPT-5.6 Terra | Olmo 7b Instruct | |
|---|---|---|
| Provider | OpenAI | Allen Institute for AI (Ai2) |
| Noometry Index | 59.1 | 29.7 |
| Released | 2026-07-09 | — |
| Weights | Proprietary | Open |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $2 | — |
| Output $ / M tokens | $12 | — |
| Results tracked | 52 | 10 |
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Category by category
Coding GPT-5.6 Terra leads
GPT-5.6 Terra: 57.1 (#16), Olmo 7b Instruct: 29.1 (#298)
| Benchmark | GPT-5.6 Terra | Olmo 7b Instruct |
|---|---|---|
| LMArena Coding | 1484 | 1016 |
| DeepSWE | 69.6% | — |
| FrontierCode | 41.3% | — |
| CursorBench | 41.3% | — |
| LMArena WebDev | 1520 | — |
| SciCode | 55% | — |
| WeirdML | 78.3% | — |
| ALE-Bench | 1,951 | — |
Agentic & Tool Use Not comparable
GPT-5.6 Terra: 40.2 (#23), Olmo 7b Instruct: —
| Benchmark | GPT-5.6 Terra | Olmo 7b Instruct |
|---|---|---|
| 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: 60.6 (#19), Olmo 7b Instruct: 18.0 (#273)
| Benchmark | GPT-5.6 Terra | Olmo 7b Instruct |
|---|---|---|
| LMArena Hard Prompts | 1467 | 993 |
| 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% | — |
| Chess Puzzles | 54% | — |
| Mystery Game Puzzles | 35% | — |
| DTBench | 93.3% | — |
| LMCA | 55% | — |
| Surface Evolver Bench | 83.8% | — |
| Epoch Capabilities Index | 159.31 | — |
Math GPT-5.6 Terra leads
GPT-5.6 Terra: 81.5 (#10), Olmo 7b Instruct: 27.8 (#234)
| Benchmark | GPT-5.6 Terra | Olmo 7b Instruct |
|---|---|---|
| LMArena Math | 1463 | 1018 |
| FrontierMath (Tiers 1-3) | 86% | — |
| FrontierMath Tier 4 | 70.7% | — |
| OTIS Mock AIME 2024-2025 | 99.7% | — |
| ProofBench | 74% | — |
Knowledge Not comparable
GPT-5.6 Terra: 61.3 (#27), Olmo 7b Instruct: —
| Benchmark | GPT-5.6 Terra | Olmo 7b Instruct |
|---|---|---|
| GPQA Diamond | 93.3% | — |
| SimpleQA Verified | 43.2% | — |
| LMArena Expert | 1492 | — |
Multimodal Not comparable
GPT-5.6 Terra: 47.5 (#10), Olmo 7b Instruct: —
| Benchmark | GPT-5.6 Terra | Olmo 7b Instruct |
|---|---|---|
| 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: 54.5 (#42), Olmo 7b Instruct: 24.1 (#286)
| Benchmark | GPT-5.6 Terra | Olmo 7b Instruct |
|---|---|---|
| LMArena Non-English | 1439 | 977 |
| LMArena Chinese | 1514 | 1013 |
| LMArena Russian | 1450 | 946 |
| LMArena French | 1476 | — |
| LMArena German | 1462 | — |
| LMArena Japanese | 1446 | — |
| LMArena Korean | 1420 | — |
| LMArena Spanish | 1455 | — |
Instruction Following GPT-5.6 Terra leads
GPT-5.6 Terra: 76.6 (#38), Olmo 7b Instruct: 49.3 (#296)
| Benchmark | GPT-5.6 Terra | Olmo 7b Instruct |
|---|---|---|
| LMArena Instruction Following | 1453 | 978 |
Long Context Not comparable
GPT-5.6 Terra: 44.4 (#64), Olmo 7b Instruct: —
| Benchmark | GPT-5.6 Terra | Olmo 7b Instruct |
|---|---|---|
| LMArena Longer Query | 1452 | — |
Writing & Preference GPT-5.6 Terra leads
GPT-5.6 Terra: 70.4 (#21), Olmo 7b Instruct: 26.0 (#298)
| Benchmark | GPT-5.6 Terra | Olmo 7b Instruct |
|---|---|---|
| LMArena Text | 1446 | 1032 |
| LMArena Creative Writing | 1411 | 990 |
| LMArena Multi-Turn | 1451 | 1007 |
| EQ-Bench Creative Writing | 1855 | — |
| EQ-Bench 4 | 1234 | — |
Frequently asked questions
Is GPT-5.6 Terra better than Olmo 7b Instruct?
GPT-5.6 Terra is the stronger model overall, scoring 59.1 to 29.7 on the Noometry Index.
Is GPT-5.6 Terra or Olmo 7b Instruct better for coding?
GPT-5.6 Terra scores higher on coding benchmarks: 57.1 versus 29.1 in the Noometry coding category.
How many benchmarks do GPT-5.6 Terra and Olmo 7b Instruct share?
10 benchmarks have published results for both models. GPT-5.6 Terra has 52 scored results on Noometry and Olmo 7b Instruct has 10.