Model comparison
Gemini 3.7 Flash vs GPT-5.6 Terra
Gemini 3.7 Flash and GPT-5.6 Terra score almost the same on the Noometry Index (59.8 vs 59.2), so choose on price, context window or the category you care about most.
Last verified . 42 shared benchmarks.
Summary
- They share 42 benchmarks with published results for both. Gemini 3.7 Flash scores higher in 7 categories and GPT-5.6 Terra in 3 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Terra leads 81.6 to 69.6.
- The biggest single-benchmark swing is FrontierMath Tier 4: 36.6% for Gemini 3.7 Flash and 70.7% for GPT-5.6 Terra.
- Gemini 3.7 Flash is cheaper at $0.75 / $3.75 per million input/output tokens, against $2 / $12 for GPT-5.6 Terra.
- GPT-5.6 Terra accepts more context: 1.05M tokens versus 1.05M.
Side by side
| Gemini 3.7 Flash | GPT-5.6 Terra | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 59.8 | 59.2 |
| Released | 2026-08-13 | 2026-07-09 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 66K | 128K |
| Input $ / M tokens | $0.75 | $2 |
| Output $ / M tokens | $3.75 | $12 |
| Results tracked | 44 | 52 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5.6 Terra leads
Gemini 3.7 Flash: 56.2 (#22), GPT-5.6 Terra: 57.7 (#19)
| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| DeepSWE | 65.5% | 69.6% |
| FrontierCode | 43.6% | 41.3% |
| LMArena WebDev | 1592 | 1522 |
| SciCode | 59.8% | 55% |
| LMArena Coding | 1497 | 1484 |
| ALE-Bench | 904.3 | 1,951 |
| CursorBench | — | 41.3% |
| FrontierSWE | 20.3% | — |
| WeirdML | — | 78.3% |
Agentic & Tool Use Gemini 3.7 Flash leads
Gemini 3.7 Flash: 42.1 (#19), GPT-5.6 Terra: 40.1 (#25)
| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| APEX-Agents | 67.8% | 58.2% |
| GDP.pdf | 23.8% | 24.7% |
| Remote Labor Index | 5% | — |
| BALROG | — | 53.2% |
| Vending-Bench 2 | — | 7,343 |
Reasoning Gemini 3.7 Flash leads
Gemini 3.7 Flash: 70.0 (#15), GPT-5.6 Terra: 60.7 (#21)
| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| ARC-AGI-2 | 84.6% | 83.9% |
| NYT Connections (extended) | 94% | 78.4% |
| ARC-AGI-1 | 95.5% | 96.5% |
| CritPt | 14.3% | 30% |
| Chess Puzzles | 47% | 54% |
| LMArena Hard Prompts | 1494 | 1468 |
| Mystery Game Puzzles | 37% | 35% |
| DTBench | 96.8% | 93.3% |
| LMCA | 50.4% | 55% |
| Epoch Capabilities Index | 157.27 | 159.62 |
| SimpleBench | — | 48.9% |
| Kagi LLM Benchmark | — | 51.3% |
| Surface Evolver Bench | — | 83.8% |
Math GPT-5.6 Terra leads
Gemini 3.7 Flash: 69.6 (#23), GPT-5.6 Terra: 81.6 (#12)
| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| FrontierMath (Tiers 1-3) | 71.6% | 86% |
| FrontierMath Tier 4 | 36.6% | 70.7% |
| OTIS Mock AIME 2024-2025 | 97.2% | 99.7% |
| ProofBench | 58% | 74% |
| LMArena Math | 1507 | 1466 |
Knowledge Gemini 3.7 Flash leads
Gemini 3.7 Flash: 69.7 (#5), GPT-5.6 Terra: 61.2 (#30)
| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| GPQA Diamond | 94.8% | 93.3% |
| SimpleQA Verified | 69.2% | 43.2% |
| LMArena Expert | 1508 | 1492 |
Multimodal GPT-5.6 Terra leads
Gemini 3.7 Flash: 37.3 (#73), GPT-5.6 Terra: 47.3 (#11)
| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| LMArena Vision | 1316 | 1271 |
| Furniture Assembly | 26.7% | 54.2% |
| Blueprint-Bench 2 | — | 30.8% |
| LMArena Document | — | 1472 |
Multilingual Gemini 3.7 Flash leads
Gemini 3.7 Flash: 57.6 (#7), GPT-5.6 Terra: 54.4 (#44)
| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| LMArena Non-English | 1484 | 1439 |
| LMArena Chinese | 1548 | 1513 |
| LMArena French | 1505 | 1471 |
| LMArena German | 1498 | 1460 |
| LMArena Japanese | 1512 | 1457 |
| LMArena Korean | 1483 | 1425 |
| LMArena Russian | 1516 | 1450 |
| LMArena Spanish | 1503 | 1448 |
Instruction Following Gemini 3.7 Flash leads
Gemini 3.7 Flash: 77.7 (#15), GPT-5.6 Terra: 76.4 (#40)
| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| LMArena Instruction Following | 1483 | 1454 |
Long Context Gemini 3.7 Flash leads
Gemini 3.7 Flash: 45.7 (#30), GPT-5.6 Terra: 44.4 (#68)
| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| LMArena Longer Query | 1492 | 1451 |
Writing & Preference Too close to call
Gemini 3.7 Flash: 71.2 (#20), GPT-5.6 Terra: 70.2 (#23)
| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| LMArena Text | 1486 | 1447 |
| LMArena Creative Writing | 1490 | 1410 |
| EQ-Bench Creative Writing | 1723 | 1855 |
| LMArena Multi-Turn | 1489 | 1449 |
| EQ-Bench 4 | — | 1234 |
Frequently asked questions
Is Gemini 3.7 Flash better than GPT-5.6 Terra?
Gemini 3.7 Flash and GPT-5.6 Terra score almost the same on the Noometry Index (59.8 vs 59.2), so choose on price, context window or the category you care about most.
Which is cheaper, Gemini 3.7 Flash or GPT-5.6 Terra?
Gemini 3.7 Flash is cheaper. It lists at $0.75 per million input tokens and $3.75 per million output tokens; GPT-5.6 Terra lists at $2 and $12.
Is Gemini 3.7 Flash or GPT-5.6 Terra better for coding?
GPT-5.6 Terra scores higher on coding benchmarks: 57.7 versus 56.2 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Terra does, with 1.05M tokens against 1.05M.
How many benchmarks do Gemini 3.7 Flash and GPT-5.6 Terra share?
42 benchmarks have published results for both models. Gemini 3.7 Flash has 44 scored results on Noometry and GPT-5.6 Terra has 52.