DeepSeek V4.1 Flash vs GPT-6.1 Terra
GPT-6.1 Terra leads DeepSeek V4.1 Flash on coding, 77.4 to 56.6 on the Vibe Coding Index, and DeepSeek V4.1 Flash costs 5.5x less per output token ($0.9085 vs $5.00 per million). Updated October 29, 2026; 23 benchmarks have a result for both.
DeepSeek V4.1 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 56.6 for DeepSeek V4.1 Flash.
Pick DeepSeek V4.1 Flash for output tokens 5.5x cheaper ($0.9085 vs $5.00 per million) and work measured by Vibe Code Bench (Vals AI) or Tax Agent Bench (Vals AI), where it leads.
- Shared results
- 23
- DeepSeek V4.1 Flash only
- 71
- 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 56.6.
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
Web design
Design Arena: websites
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 1308 against 1283.
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
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash $0.0007, GPT-6.1 Terra $0.0035 per turn.
List prices
At a glance
- Coding index
- DeepSeek V4.1 Flash 56.6 from 4 benchmarks, GPT-6.1 Terra 77.4 from 4 benchmarks.
- Widest category
- Math, 30.3 points apart on average over 3 shared benchmarks.
- Widest single gap
- FrontierMath, tier 4: DeepSeek V4.1 Flash 26.8% against GPT-6.1 Terra 92.7%, 65.9 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash $0.9085 against GPT-6.1 Terra $5.00 per million output tokens, 5.5x apart.
- Context window
- DeepSeek V4.1 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 | DeepSeek V4.1 Flash | Bars | GPT-6.1 Terra | Ties |
|---|---|---|---|---|
| Coding | 1 | 6 | ||
| Agentic work | 2 | 1 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 1 | ||
| Web design | 3 | 1 | ||
| General | 1 | 1 | ||
| All shared boards | 7 | 16 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index16
| Benchmark | DeepSeek V4.1 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 94.3% | Only GPT-6.1 Terra measured |
| LMArena WebDev | 1619 | 1673 | GPT-6.1 Terra |
| Terminal-Bench 4 (Vals AI) | 19.7% | 49.5% | GPT-6.1 Terra |
| Vibe Code Bench (Vals AI) | 84.7% | 84.0% | DeepSeek V4.1 Flash |
| Code migration (Vals AI) | 45.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| IOI (Vals AI) | 40.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 74.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| SWE-bench Multimodal (Vals AI) | 46.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench 1-100 (Vals AI) | 16.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| SkillsBench (Vals AI) | 69.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| CyberBench (Vals AI) | 73.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| SciCode | 51.9% | 55.1% | GPT-6.1 Terra |
| FrontierCode | 43.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| ALE-Bench | 1092.3 | 2608.8 | GPT-6.1 Terra |
| LMArena Text: coding | 1501 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: software and IT | 1496 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev: React | 1629 | 1657 | GPT-6.1 Terra |
| LMArena WebDev: HTML | 1613 | 1719 | GPT-6.1 Terra |
| LMArena WebDev: from an image | 1606 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 51.0 | Only GPT-6.1 Terra measured |
| Epoch Capabilities Index | 155.9 | Not measured | Only DeepSeek V4.1 Flash measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | DeepSeek V4.1 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| 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 |
| SREBench (Vals AI) | 0.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Finance Agent (Vals AI) | 53.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Tax Agent Bench (Vals AI) | 26.6% | 15.2% | DeepSeek V4.1 Flash |
| Legal Research Bench (Vals AI) | 41.4% | 26.0% | DeepSeek V4.1 Flash |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 1.7% | Only GPT-6.1 Terra measured |
| Excel Modeling Benchmark (Vals AI) | 57.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| BioMysteryBench (Vals AI) | 67.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vals Science Index | 29.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| APEX-Agents | 39.5% | 68.3% | GPT-6.1 Terra |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V4.1 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 88.7% | Only GPT-6.1 Terra measured |
| MysteryMechanism (Vals AI) | 21.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.2% | 46.2% | GPT-6.1 Terra |
| GPQA Diamond (Epoch AI run) | 89.8% | 94.3% | GPT-6.1 Terra |
| ARC-AGI | 94.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| ARC-AGI-2 | 72.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| Chess puzzles | 48.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Mystery game puzzles | 43.0% | 74.0% | GPT-6.1 Terra |
| EBR-bench | Not measured | 78.1% | Only GPT-6.1 Terra measured |
| LMArena Text: hard prompts | 1483 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: expert | 1502 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: hard prompts in English | 1488 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: diagrams | 1297 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: homework | 1307 | Not measured | Only DeepSeek V4.1 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 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V4.1 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | 100.0% | GPT-6.1 Terra |
| FrontierMath, tiers 1 to 3 | 67.4% | 90.9% | GPT-6.1 Terra |
| FrontierMath, tier 4 | 26.8% | 92.7% | GPT-6.1 Terra |
| ProofBench | 54.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: math | 1481 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: mathematical work | 1484 | Not measured | Only DeepSeek V4.1 Flash measured |
| MathArena | 42.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V4.1 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedCode (Vals AI) | 41.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| SimpleQA Verified | 42.9% | 57.3% | GPT-6.1 Terra |
| LMArena Text: science | 1471 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: medicine and healthcare | 1486 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: legal and government | 1446 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: business and finance | 1462 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | DeepSeek V4.1 Flash | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Design Arena: websites | 1308 | 1283 | DeepSeek V4.1 Flash |
| Design Arena: UI components | 1309 | 1277 | DeepSeek V4.1 Flash |
| Design Arena: game dev | 1330 | 1348 | GPT-6.1 Terra |
| Design Arena: data viz | 1292 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: 3D | 1354 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: all code categories | 1318 | 1295 | DeepSeek V4.1 Flash |
| Design Arena: SVG | 1242 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: ASCII art | 1265 | Not measured | Only DeepSeek V4.1 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 index11
| Benchmark | DeepSeek V4.1 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) | 64.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| SAGE (Vals AI) | 85.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedScribe (Vals AI) | 85.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Long context reasoning (AA-LCR) | 84.0% | 82.7% | DeepSeek V4.1 Flash |
| DTBench | 89.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMCA | 47.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Surface Evolver Bench | 46.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Furniture assembly | 34.2% | 79.2% | GPT-6.1 Terra |
| LMArena Text | 1465 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: instruction following | 1474 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: creative writing | 1437 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision | 1278 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: English | 1475 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: non-English | 1450 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Chinese | 1502 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: German | 1466 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Japanese | 1428 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Korean | 1432 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: French | 1467 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Spanish | 1458 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Russian | 1467 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Polish | 1458 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: multi-turn | 1460 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: longer queries | 1474 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: writing and language | 1451 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: entertainment and media | 1445 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: English | 1288 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: Chinese | 1327 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: reading text | 1282 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: humor | 1260 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: creative writing | 1275 | Not measured | Only DeepSeek V4.1 Flash measured |
| MultiChallenge | Not measured | 74.2% | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4.1 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
DeepSeek V4.1 Flash costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 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 | DeepSeek V4.1 Flash | OpenAI GPT-6.1 Terra |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | September 10, 2026 | October 26, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.21 | $1.00 |
| Output $/Mtok | $0.9085 | $5.00 |
| Coding index | 56.6 | 77.4 |
| Independent measurements behind it | 4 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 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 56.6 for DeepSeek V4.1 Flash. Pick DeepSeek V4.1 Flash for output tokens 5.5x cheaper ($0.9085 vs $5.00 per million) and work measured by Vibe Code Bench (Vals AI) or Tax Agent Bench (Vals AI), where it leads.
Which is cheaper, DeepSeek V4.1 Flash or GPT-6.1 Terra?
DeepSeek V4.1 Flash costs $0.21 per million input tokens and $0.9085 per million output tokens; GPT-6.1 Terra costs $1.00 and $5.00. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V4.1 Flash or GPT-6.1 Terra?
GPT-6.1 Terra, with 1.05M tokens against 1.05M.
How many benchmarks is the DeepSeek V4.1 Flash vs GPT-6.1 Terra comparison based on?
23 benchmarks have a result for both models as of October 29, 2026. DeepSeek V4.1 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.