Gemini 3.5 Flash vs GPT-6.1 Terra
GPT-6.1 Terra leads Gemini 3.5 Flash on coding, 77.4 to 39.8 on the Vibe Coding Index, and GPT-6.1 Terra costs 1.8x less per output token ($5.00 vs $9.00 per million). Updated October 29, 2026; 23 benchmarks have a result for both.
vs boards won of 23 shared
Gemini 3.5 Flash or GPT-6.1 Terra: which to pick
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 39.8 for Gemini 3.5 Flash.
Pick Gemini 3.5 Flash for work measured by Tax Agent Bench (Vals AI) or Legal Research Bench (Vals AI), where it leads.
Model AGemini 3.5 FlashGoogle39.8/1004 independent benchmarks$1.21 per solved taskModel BGPT-6.1 TerraOpenAI77.4/1004 independent benchmarksNo cost per solved task
- Shared results
- 23
- Gemini 3.5 Flash only
- 93
- GPT-6.1 Terra only
- 13
- Like-for-like categories
- 7 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
GPT-6.1 Terra
GPT-6.1 Terra scores 77.4 against 39.8.
4 benchmarks behind each score
Intelligence
AA Intelligence Index
No call
Only GPT-6.1 Terra has a AA Intelligence Index result, 51.0.
Directional only
Agentic work
AA Agentic Index
No call
Only Gemini 3.5 Flash has a AA Agentic Index result, 26.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Gemini 3.5 Flash has a GPQA Diamond result, 92.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.5 Flash has a MMLU Pro result, 89.5%.
Directional only
Web design
Design Arena: websites
GPT-6.1 Terra
GPT-6.1 Terra leads, 1283 against 1266.
Same board, both measured
General
Vals Index
No call
Only GPT-6.1 Terra has a Vals Index result, 60.5%.
Directional only
Long documents
Listed context window
GPT-6.1 Terra
GPT-6.1 Terra takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6.1 Terra
Gemini 3.5 Flash $0.0060, GPT-6.1 Terra $0.0035 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.5 Flash has the number, $1.21.
Directional only
At a glance
- Coding index
- Gemini 3.5 Flash 39.8 from 4 benchmarks, GPT-6.1 Terra 77.4 from 4 benchmarks.
- Widest category
- Math, 32.8 points apart on average over 3 shared benchmarks.
- Widest single gap
- EBR-bench: Gemini 3.5 Flash 4.8% against GPT-6.1 Terra 78.1%, 73.3 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.5 Flash $9.00 against GPT-6.1 Terra $5.00 per million output tokens, 1.8x apart.
- Context window
- Gemini 3.5 Flash takes 1.05M tokens, GPT-6.1 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 3.5 Flash | Bars | GPT-6.1 Terra | Ties |
|---|---|---|---|---|
| Coding | 0 | 7 | ||
| Agentic work | 2 | 1 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 3 | ||
| Knowledge | 1 | 0 | ||
| Web design | 0 | 4 | ||
| General | 0 | 1 | ||
| All shared boards | 3 | 20 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index07
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 94.3% | Only GPT-6.1 Terra measured |
| LMArena WebDev | 1499 | 1673 | GPT-6.1 Terra |
| AA Coding Index | 70.1 | Not measured | Only Gemini 3.5 Flash measured |
| LiveCodeBench (Vals AI) | 87.6% | Not measured | Only Gemini 3.5 Flash measured |
| SWE-bench Verified (Vals AI) | 78.8% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench 4 (Vals AI) | 6.1% | 49.5% | GPT-6.1 Terra |
| Vibe Code Bench (Vals AI) | 48.7% | 84.0% | GPT-6.1 Terra |
| Code migration (Vals AI) | 26.8% | Not measured | Only Gemini 3.5 Flash measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 74.2% | Not measured | Only Gemini 3.5 Flash measured |
| SkillsBench (Vals AI) | 52.7% | Not measured | Only Gemini 3.5 Flash measured |
| SciCode | 53.9% | 55.1% | GPT-6.1 Terra |
| Terminal-Bench Hard (Artificial Analysis run) | 46.2% | Not measured | Only Gemini 3.5 Flash measured |
| WeirdML | 62.6% | Not measured | Only Gemini 3.5 Flash measured |
| ALE-Bench | 911.0 | 2608.8 | GPT-6.1 Terra |
| LMArena Text: coding | 1493 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: software and IT | 1494 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena WebDev: React | 1495 | 1657 | GPT-6.1 Terra |
| LMArena WebDev: HTML | 1522 | 1719 | GPT-6.1 Terra |
| LMArena WebDev: from an image | 1504 | Not measured | Only Gemini 3.5 Flash measured |
| SciCode | 12.3% | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 51.0 | Only GPT-6.1 Terra measured |
| Epoch Capabilities Index | 154.9 | Not measured | Only Gemini 3.5 Flash measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| AA Agentic Index | 26.0 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building web apps | 1203 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building full-stack apps | 1197 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building mobile apps | 1176 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building Android apps | 1182 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building Godot games | 1098 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building games | 1144 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: HTML slides | 1039 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: PowerPoint slides | 1136 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: spreadsheets | 1081 | Not measured | Only Gemini 3.5 Flash measured |
| LiveBench research | Not measured | 73.9% | Only GPT-6.1 Terra measured |
| LiveBench browser | Not measured | 93.1% | Only GPT-6.1 Terra measured |
| LiveBench long agentic | Not measured | 48.6% | Only GPT-6.1 Terra measured |
| Finance Agent (Vals AI) | 57.9% | Not measured | Only Gemini 3.5 Flash measured |
| Tax Agent Bench (Vals AI) | 21.6% | 15.2% | Gemini 3.5 Flash |
| Legal Research Bench (Vals AI) | 30.8% | 26.0% | Gemini 3.5 Flash |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 1.7% | Only GPT-6.1 Terra measured |
| Excel Modeling Benchmark (Vals AI) | 63.5% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | Not measured | Only Gemini 3.5 Flash measured |
| τ²-Bench Telecom | 95.6% | Not measured | Only Gemini 3.5 Flash measured |
| APEX-Agents | 27.5% | 68.3% | GPT-6.1 Terra |
| Vending-Bench 2 | $5,396 | Not measured | Only Gemini 3.5 Flash measured |
| MCP Atlas | 83.6% | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| GPQA Diamond | 92.7% | Not measured | Only Gemini 3.5 Flash measured |
| LiveBench reasoning | Not measured | 88.7% | Only GPT-6.1 Terra measured |
| MMMU Pro (Vals AI) | 88.3% | Not measured | Only Gemini 3.5 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 92.2% | Not measured | Only Gemini 3.5 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 42.7% | 46.2% | GPT-6.1 Terra |
| GPQA Diamond (Epoch AI run) | 92.8% | 94.3% | GPT-6.1 Terra |
| ARC-AGI | 92.5% | Not measured | Only Gemini 3.5 Flash measured |
| ARC-AGI-2 | 72.1% | Not measured | Only Gemini 3.5 Flash measured |
| SimpleBench | 76.7% | Not measured | Only Gemini 3.5 Flash measured |
| Chess puzzles | 45.0% | Not measured | Only Gemini 3.5 Flash measured |
| Mystery game puzzles | 32.0% | 74.0% | GPT-6.1 Terra |
| EBR-bench | 4.8% | 78.1% | GPT-6.1 Terra |
| LMArena Text: hard prompts | 1488 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: expert | 1494 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: hard prompts in English | 1482 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: diagrams | 1323 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: homework | 1330 | Not measured | Only Gemini 3.5 Flash measured |
| Humanity's Last Exam (Scale run) | Not measured | 35.7% | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| OTIS Mock AIME | 95.6% | 100.0% | GPT-6.1 Terra |
| FrontierMath, tiers 1 to 3 | 62.8% | 90.9% | GPT-6.1 Terra |
| FrontierMath, tier 4 | 26.8% | 92.7% | GPT-6.1 Terra |
| ProofBench | 31.0% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: math | 1504 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: mathematical work | 1494 | Not measured | Only Gemini 3.5 Flash measured |
| MathArena | 24.5% | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| MMLU Pro | 89.5% | Not measured | Only Gemini 3.5 Flash measured |
| LegalBench (Vals AI) | 83.6% | Not measured | Only Gemini 3.5 Flash measured |
| CorpFin (Vals AI) | 64.7% | Not measured | Only Gemini 3.5 Flash measured |
| TaxEval (Vals AI) | 74.4% | Not measured | Only Gemini 3.5 Flash measured |
| MortgageTax (Vals AI) | 68.1% | Not measured | Only Gemini 3.5 Flash measured |
| MedCode (Vals AI) | 55.8% | Not measured | Only Gemini 3.5 Flash measured |
| SimpleQA Verified | 66.2% | 57.3% | Gemini 3.5 Flash |
| LMArena Text: science | 1495 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: medicine and healthcare | 1484 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: legal and government | 1487 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: business and finance | 1467 | Not measured | Only Gemini 3.5 Flash measured |
| FACTS Benchmark Suite | 52.9% | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Design Arena: websites | 1266 | 1283 | GPT-6.1 Terra |
| Design Arena: UI components | 1267 | 1277 | GPT-6.1 Terra |
| Design Arena: game dev | 1262 | 1348 | GPT-6.1 Terra |
| Design Arena: data viz | 1239 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: 3D | 1240 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: all code categories | 1265 | 1295 | GPT-6.1 Terra |
| Design Arena: SVG | 1252 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: ASCII art | 1251 | Not measured | Only Gemini 3.5 Flash measured |
| LiveBench design | Not measured | 82.3% | Only GPT-6.1 Terra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 3.5 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Vals Index | Not measured | 60.5% | Only GPT-6.1 Terra measured |
| LiveBench data analysis | Not measured | 82.3% | Only GPT-6.1 Terra measured |
| Public Benefits Bench (Vals AI) | 59.5% | Not measured | Only Gemini 3.5 Flash measured |
| MedScribe (Vals AI) | 76.6% | Not measured | Only Gemini 3.5 Flash measured |
| Vals Multimodal Index | 62.9% | Not measured | Only Gemini 3.5 Flash measured |
| IFBench | 76.3% | Not measured | Only Gemini 3.5 Flash measured |
| Long context reasoning (AA-LCR) | 74.3% | 82.7% | GPT-6.1 Terra |
| DTBench | 94.7% | Not measured | Only Gemini 3.5 Flash measured |
| LMCA | 47.1% | Not measured | Only Gemini 3.5 Flash measured |
| Surface Evolver Bench | 58.1% | Not measured | Only Gemini 3.5 Flash measured |
| Furniture assembly | Not measured | 79.2% | Only GPT-6.1 Terra measured |
| LMArena Text | 1482 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: instruction following | 1467 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: creative writing | 1471 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision | 1308 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: English | 1481 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: non-English | 1476 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Chinese | 1527 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: German | 1493 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Japanese | 1490 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Korean | 1448 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: French | 1489 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Spanish | 1481 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Russian | 1494 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Polish | 1517 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: multi-turn | 1481 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: longer queries | 1483 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: writing and language | 1478 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: entertainment and media | 1460 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: English | 1305 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: Chinese | 1377 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: reading text | 1317 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: humor | 1321 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: creative writing | 1301 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Document | 1463 | Not measured | Only Gemini 3.5 Flash measured |
| MultiChallenge | Not measured | 74.2% | Only GPT-6.1 Terra measured |
| EQ-Bench 4 | 1077 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.5 Flash | GPT-6.1 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 3.5 Flash$0.0060Fits in one request
GPT-6.1 Terra$0.0035Fits in one request
GPT-6.1 Terra costs less
Repository review
50K input + 3K output tokens
Gemini 3.5 Flash$0.102Fits in one request
GPT-6.1 Terra$0.065Fits in one request
GPT-6.1 Terra costs less
Agent loop
200K input + 10K output tokens
Gemini 3.5 Flash$0.390Fits in one request
GPT-6.1 Terra$0.250Fits in one request
GPT-6.1 Terra 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 3.5 Flash | OpenAI GPT-6.1 Terra |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | May 19, 2026 | October 26, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.50 | $1.00 |
| Output $/Mtok | $9.00 | $5.00 |
| Coding index | 39.8 | 77.4 |
| Independent measurements behind it | 4 | 4 |
| Cost per solved task | $1.21 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.5 Flash better than GPT-6.1 Terra for coding?
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 39.8 for Gemini 3.5 Flash. Pick Gemini 3.5 Flash for work measured by Tax Agent Bench (Vals AI) or Legal Research Bench (Vals AI), where it leads.
Which is cheaper, Gemini 3.5 Flash or GPT-6.1 Terra?
Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; GPT-6.1 Terra costs $1.00 and $5.00. Cost per solved task is known for Gemini 3.5 Flash only.
Which has the bigger context window, Gemini 3.5 Flash or GPT-6.1 Terra?
GPT-6.1 Terra, with 1.05M tokens against 1.05M.
How many benchmarks is the Gemini 3.5 Flash vs GPT-6.1 Terra comparison based on?
23 benchmarks have a result for both models as of October 29, 2026. Gemini 3.5 Flash's coding index rests on 4 independent benchmarks and GPT-6.1 Terra's on 4. Where only one model has a result, the page says so instead of naming a winner.