Gemini 2.5 Flash vs GPT-5.6 Terra
GPT-5.6 Terra leads Gemini 2.5 Flash on the Artificial Analysis Intelligence Index, 42.1 to 15.5, and Gemini 2.5 Flash costs 4.8x less per output token ($2.50 vs $12.00 per million). Updated October 22, 2026; 63 benchmarks have a result for both.
Gemini 2.5 Flash or GPT-5.6 Terra: which to pick
Only GPT-5.6 Terra has a coding score, 63.9 on the Vibe Coding Index; Gemini 2.5 Flash has none, so the two cannot be ranked on coding.
Pick Gemini 2.5 Flash for output tokens 4.8x cheaper ($2.50 vs $12.00 per million) and work measured by Kagi LLM Benchmark or MedScribe (Vals AI), where it leads.
- Shared results
- 63
- Gemini 2.5 Flash only
- 10
- GPT-5.6 Terra only
- 64
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only GPT-5.6 Terra has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.6 Terra
GPT-5.6 Terra leads, 42.1 against 15.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Terra has a AA Agentic Index result, 43.2.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Terra has a GPQA Diamond result, 90.9%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Terra has a MMLU Pro result, 86.7%.
Directional only
Web design
Design Arena: websites
GPT-5.6 Terra
GPT-5.6 Terra leads, 1268 against 1074.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Terra
GPT-5.6 Terra takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 2.5 Flash
Gemini 2.5 Flash $0.0015, GPT-5.6 Terra $0.0080 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.6 Terra
Gemini 2.5 Flash $0.466, GPT-5.6 Terra $0.42.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 2.5 Flash not benchmarked, GPT-5.6 Terra 63.9 from 6 benchmarks.
- Widest category
- Agentic work, 38.9 points apart on average over 3 shared benchmarks.
- Widest single gap
- ARC-AGI-2: Gemini 2.5 Flash 2.5% against GPT-5.6 Terra 83.9%, 81.4 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash $2.50 against GPT-5.6 Terra $12.00 per million output tokens, 4.8x apart.
- Context window
- Gemini 2.5 Flash takes 1.05M tokens, GPT-5.6 Terra 1.05M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Gemini 2.5 Flash | Bars | GPT-5.6 Terra | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 3 | ||
| Reasoning | 1 | 10 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 6 | ||
| Web design | 0 | 7 | ||
| General | 1 | 28 | ||
| All shared boards | 2 | 61 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Terra | Leader |
|---|---|---|---|
| SWE-bench Verified | 28.7% | Not measured | Only Gemini 2.5 Flash measured |
| LiveBench coding | Not measured | 86.2% | Only GPT-5.6 Terra measured |
| LMArena WebDev | Not measured | 1522 | Only GPT-5.6 Terra measured |
| AA Coding Index | Not measured | 76.7 | Only GPT-5.6 Terra measured |
| LiveCodeBench (Vals AI) | Not measured | 85.9% | Only GPT-5.6 Terra measured |
| SWE-bench Verified (Vals AI) | Not measured | 95.4% | Only GPT-5.6 Terra measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 22.7% | Only GPT-5.6 Terra measured |
| Vibe Code Bench (Vals AI) | Not measured | 74.6% | Only GPT-5.6 Terra measured |
| Code migration (Vals AI) | Not measured | 47.8% | Only GPT-5.6 Terra measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only GPT-5.6 Terra measured |
| IOI (Vals AI) | Not measured | 87.6% | Only GPT-5.6 Terra measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 77.5% | Only GPT-5.6 Terra measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 14.8% | Only GPT-5.6 Terra measured |
| SkillsBench (Vals AI) | Not measured | 58.9% | Only GPT-5.6 Terra measured |
| CyberBench (Vals AI) | Not measured | 72.1% | Only GPT-5.6 Terra measured |
| LiveCodeBench (Artificial Analysis run) | 69.5% | Not measured | Only Gemini 2.5 Flash measured |
| SciCode | Not measured | 55.0% | Only GPT-5.6 Terra measured |
| Terminal-Bench Hard (Artificial Analysis run) | 13.6% | 62.9% | GPT-5.6 Terra |
| Terminal-Bench | 17.1% | Not measured | Only Gemini 2.5 Flash measured |
| FrontierCode | Not measured | 41.3% | Only GPT-5.6 Terra measured |
| WeirdML | Not measured | 78.3% | Only GPT-5.6 Terra measured |
| ALE-Bench | Not measured | 1951.4 | Only GPT-5.6 Terra measured |
| LMArena Text: coding | 1423 | 1485 | GPT-5.6 Terra |
| LMArena Text: software and IT | 1425 | 1482 | GPT-5.6 Terra |
| LMArena WebDev: React | Not measured | 1513 | Only GPT-5.6 Terra measured |
| LMArena WebDev: HTML | Not measured | 1526 | Only GPT-5.6 Terra measured |
| LMArena WebDev: from an image | Not measured | 1541 | Only GPT-5.6 Terra measured |
| SciCode | Not measured | 10.8% | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 11 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Terra | Leader |
|---|---|---|---|
| AA Intelligence Index | 15.5 | 42.1 | GPT-5.6 Terra |
| Epoch Capabilities Index | 142.9 | 160.1 | GPT-5.6 Terra |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Terra | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 43.2 | Only GPT-5.6 Terra measured |
| Design Arena: agents building web apps | Not measured | 1120 | Only GPT-5.6 Terra measured |
| Design Arena: agents building full-stack apps | Not measured | 1061 | Only GPT-5.6 Terra measured |
| Design Arena: agents building mobile apps | Not measured | 1111 | Only GPT-5.6 Terra measured |
| Design Arena: agents building Android apps | Not measured | 1062 | Only GPT-5.6 Terra measured |
| Design Arena: agents building games | Not measured | 1083 | Only GPT-5.6 Terra measured |
| Design Arena: HTML slides | Not measured | 1058 | Only GPT-5.6 Terra measured |
| Design Arena: PowerPoint slides | Not measured | 1105 | Only GPT-5.6 Terra measured |
| LiveBench research | Not measured | 60.4% | Only GPT-5.6 Terra measured |
| LiveBench browser | Not measured | 84.0% | Only GPT-5.6 Terra measured |
| LiveBench long agentic | Not measured | 48.4% | Only GPT-5.6 Terra measured |
| SREBench (Vals AI) | Not measured | 9.5% | Only GPT-5.6 Terra measured |
| Finance Agent (Vals AI) | Not measured | 54.4% | Only GPT-5.6 Terra measured |
| Tax Agent Bench (Vals AI) | Not measured | 30.0% | Only GPT-5.6 Terra measured |
| Legal Research Bench (Vals AI) | Not measured | 41.4% | Only GPT-5.6 Terra measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 66.2% | Only GPT-5.6 Terra measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 10.0% | Only GPT-5.6 Terra measured |
| τ²-Bench Telecom | 31.6% | 86.3% | GPT-5.6 Terra |
| APEX-Agents | Not measured | 58.2% | Only GPT-5.6 Terra measured |
| BALROG | 33.5% | 53.2% | GPT-5.6 Terra |
| Vending-Bench 2 | $549 | $7,343 | GPT-5.6 Terra |
| Berkeley Function Calling Leaderboard (BFCL) | 56.2% | Not measured | Only Gemini 2.5 Flash measured |
| BrowseComp-Plus | 39.9% | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 18 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index110
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Terra | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 90.9% | Only GPT-5.6 Terra measured |
| LiveBench reasoning | Not measured | 90.6% | Only GPT-5.6 Terra measured |
| MMMU Pro (Vals AI) | Not measured | 86.5% | Only GPT-5.6 Terra measured |
| GPQA Diamond (Artificial Analysis run) | 79.0% | 92.5% | GPT-5.6 Terra |
| Humanity's Last Exam (Artificial Analysis run) | 12.1% | 42.9% | GPT-5.6 Terra |
| GPQA Diamond (Epoch AI run) | Not measured | 93.3% | Only GPT-5.6 Terra measured |
| ARC-AGI | 33.3% | 96.5% | GPT-5.6 Terra |
| ARC-AGI-2 | 2.5% | 83.9% | GPT-5.6 Terra |
| SimpleBench | 41.2% | 48.9% | GPT-5.6 Terra |
| Chess puzzles | Not measured | 47.0% | Only GPT-5.6 Terra measured |
| Mystery game puzzles | Not measured | 35.0% | Only GPT-5.6 Terra measured |
| LMArena Text: hard prompts | 1422 | 1469 | GPT-5.6 Terra |
| LMArena Text: expert | 1426 | 1496 | GPT-5.6 Terra |
| LMArena Text: hard prompts in English | 1420 | 1465 | GPT-5.6 Terra |
| LMArena Vision: diagrams | 1245 | 1295 | GPT-5.6 Terra |
| LMArena Vision: homework | 1244 | 1312 | GPT-5.6 Terra |
| Kagi LLM Benchmark | 56.8% | 51.3% | Gemini 2.5 Flash |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Terra | Leader |
|---|---|---|---|
| AA Math Index | 73.3 | Not measured | Only Gemini 2.5 Flash measured |
| AIME 2025 (Artificial Analysis run) | 73.3% | Not measured | Only Gemini 2.5 Flash measured |
| OTIS Mock AIME | Not measured | 99.7% | Only GPT-5.6 Terra measured |
| FrontierMath, tiers 1 to 3 | Not measured | 86.0% | Only GPT-5.6 Terra measured |
| FrontierMath, tier 4 | Not measured | 70.7% | Only GPT-5.6 Terra measured |
| ProofBench | Not measured | 74.0% | Only GPT-5.6 Terra measured |
| LMArena Text: math | 1411 | 1465 | GPT-5.6 Terra |
| LMArena Text: mathematical work | 1422 | 1478 | GPT-5.6 Terra |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Terra | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.7% | Only GPT-5.6 Terra measured |
| LegalBench (Vals AI) | Not measured | 85.1% | Only GPT-5.6 Terra measured |
| CorpFin (Vals AI) | Not measured | 65.3% | Only GPT-5.6 Terra measured |
| TaxEval (Vals AI) | Not measured | 76.2% | Only GPT-5.6 Terra measured |
| MortgageTax (Vals AI) | Not measured | 67.3% | Only GPT-5.6 Terra measured |
| MedCode (Vals AI) | 40.4% | 43.4% | GPT-5.6 Terra |
| MMLU Pro (Artificial Analysis run) | 83.2% | Not measured | Only Gemini 2.5 Flash measured |
| SimpleQA Verified | Not measured | 43.2% | Only GPT-5.6 Terra measured |
| LMArena Text: science | 1433 | 1452 | GPT-5.6 Terra |
| LMArena Text: medicine and healthcare | 1428 | 1430 | GPT-5.6 Terra |
| LMArena Text: legal and government | 1430 | 1461 | GPT-5.6 Terra |
| LMArena Text: business and finance | 1404 | 1448 | GPT-5.6 Terra |
| FACTS Benchmark Suite | 47.2% | 52.0% | GPT-5.6 Terra |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Terra | Leader |
|---|---|---|---|
| Design Arena: websites | 1074 | 1268 | GPT-5.6 Terra |
| Design Arena: UI components | 1002 | 1256 | GPT-5.6 Terra |
| Design Arena: game dev | 1004 | 1229 | GPT-5.6 Terra |
| Design Arena: data viz | 1060 | 1240 | GPT-5.6 Terra |
| Design Arena: 3D | 1020 | 1134 | GPT-5.6 Terra |
| Design Arena: all code categories | 1059 | 1241 | GPT-5.6 Terra |
| Design Arena: SVG | 1020 | 1219 | GPT-5.6 Terra |
| Design Arena: ASCII art | Not measured | 1177 | Only GPT-5.6 Terra measured |
| LiveBench design | Not measured | 76.0% | Only GPT-5.6 Terra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index128
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Terra | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 79.3% | Only GPT-5.6 Terra measured |
| Public Benefits Bench (Vals AI) | Not measured | 62.4% | Only GPT-5.6 Terra measured |
| SAGE (Vals AI) | 44.8% | 47.0% | GPT-5.6 Terra |
| MedScribe (Vals AI) | 83.0% | 82.9% | Gemini 2.5 Flash |
| Vals Multimodal Index | Not measured | 65.1% | Only GPT-5.6 Terra measured |
| IFBench | 50.3% | 71.2% | GPT-5.6 Terra |
| Long context reasoning (AA-LCR) | 65.3% | 83.0% | GPT-5.6 Terra |
| DTBench | 76.5% | 93.3% | GPT-5.6 Terra |
| LMCA | 27.5% | 54.9% | GPT-5.6 Terra |
| Surface Evolver Bench | Not measured | 83.8% | Only GPT-5.6 Terra measured |
| Furniture assembly | Not measured | 54.2% | Only GPT-5.6 Terra measured |
| LMArena Text | 1417 | 1448 | GPT-5.6 Terra |
| LMArena Text: instruction following | 1405 | 1456 | GPT-5.6 Terra |
| LMArena Text: creative writing | 1400 | 1413 | GPT-5.6 Terra |
| LMArena Vision | 1235 | 1271 | GPT-5.6 Terra |
| LMArena Text: English | 1418 | 1449 | GPT-5.6 Terra |
| LMArena Text: non-English | 1409 | 1441 | GPT-5.6 Terra |
| LMArena Text: Chinese | 1449 | 1514 | GPT-5.6 Terra |
| LMArena Text: German | 1417 | 1460 | GPT-5.6 Terra |
| LMArena Text: Japanese | 1396 | 1454 | GPT-5.6 Terra |
| LMArena Text: Korean | 1385 | 1427 | GPT-5.6 Terra |
| LMArena Text: French | 1432 | 1466 | GPT-5.6 Terra |
| LMArena Text: Spanish | 1422 | 1451 | GPT-5.6 Terra |
| LMArena Text: Russian | 1415 | 1452 | GPT-5.6 Terra |
| LMArena Text: Polish | 1413 | 1446 | GPT-5.6 Terra |
| LMArena Text: multi-turn | 1408 | 1453 | GPT-5.6 Terra |
| LMArena Text: longer queries | 1419 | 1454 | GPT-5.6 Terra |
| LMArena Text: writing and language | 1405 | 1431 | GPT-5.6 Terra |
| LMArena Text: entertainment and media | 1393 | 1418 | GPT-5.6 Terra |
| LMArena Vision: English | 1239 | 1272 | GPT-5.6 Terra |
| LMArena Vision: Chinese | 1284 | 1337 | GPT-5.6 Terra |
| LMArena Vision: reading text | 1237 | 1278 | GPT-5.6 Terra |
| LMArena Vision: humor | 1225 | 1236 | GPT-5.6 Terra |
| LMArena Vision: captioning | 1277 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: recognizing things | 1252 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: creative writing | 1241 | 1248 | GPT-5.6 Terra |
| LMArena Document | Not measured | 1472 | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 9 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash | GPT-5.6 Terra | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Gemini 2.5 Flash costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Flash costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 Flash costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Google Gemini 2.5 Flash | OpenAI GPT-5.6 Terra |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | July 9, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.30 | $2.00 |
| Output $/Mtok | $2.50 | $12.00 |
| Coding index | Not benchmarked | 63.9 |
| Independent measurements behind it | 0 | 6 |
| Cost per solved task | $0.466 | $0.42 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Flash better than GPT-5.6 Terra for coding?
Only GPT-5.6 Terra has a coding score, 63.9 on the Vibe Coding Index; Gemini 2.5 Flash has none, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash for output tokens 4.8x cheaper ($2.50 vs $12.00 per million) and work measured by Kagi LLM Benchmark or MedScribe (Vals AI), where it leads.
Which is cheaper, Gemini 2.5 Flash or GPT-5.6 Terra?
Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens; GPT-5.6 Terra costs $2.00 and $12.00. Per solved SWE-bench Verified task, Gemini 2.5 Flash costs $0.466 and GPT-5.6 Terra $0.42.
Which has the bigger context window, Gemini 2.5 Flash or GPT-5.6 Terra?
GPT-5.6 Terra, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 2.5 Flash vs GPT-5.6 Terra comparison based on?
63 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Flash's coding index rests on 0 independent benchmarks and GPT-5.6 Terra's on 6. Where only one model has a result, the page says so instead of naming a winner.