DeepSeek V4 Pro 0813 vs GPT-6.1 Terra
GPT-6.1 Terra leads DeepSeek V4 Pro 0813 on coding, 77.4 to 56.1 on the Vibe Coding Index, and DeepSeek V4 Pro 0813 costs 2.5x less per output token ($1.98 vs $5.00 per million). Updated October 29, 2026; 21 benchmarks have a result for both.
DeepSeek V4 Pro 0813 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 56.1 for DeepSeek V4 Pro 0813, though on 4 benchmarks against 5.
Pick DeepSeek V4 Pro 0813 for output tokens 2.5x cheaper ($1.98 vs $5.00 per million) and work measured by Tax Agent Bench (Vals AI) or Legal Research Bench (Vals AI), where it leads.
- Shared results
- 21
- DeepSeek V4 Pro 0813 only
- 57
- GPT-6.1 Terra only
- 15
- 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 56.1.
5 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6.1 Terra
GPT-6.1 Terra leads, 51.0 against 23.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Pro 0813 has a AA Agentic Index result, 41.3.
Directional only
Reasoning
GPQA Diamond
No call
Only DeepSeek V4 Pro 0813 has a GPQA Diamond result, 92.4%.
Directional only
Knowledge
MMLU Pro
No call
Only DeepSeek V4 Pro 0813 has a MMLU Pro result, 87.0%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-6.1 Terra has a Design Arena: websites result, 1283.
Directional only
General
Vals Index
GPT-6.1 Terra
GPT-6.1 Terra leads, 60.5% against 53.0%.
Same board, both measured
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 Pro 0813
DeepSeek V4 Pro 0813 $0.0016, GPT-6.1 Terra $0.0035 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only DeepSeek V4 Pro 0813 has the number, $0.10.
Directional only
At a glance
- Coding index
- DeepSeek V4 Pro 0813 56.1 from 5 benchmarks, GPT-6.1 Terra 77.4 from 4 benchmarks.
- Widest category
- Math, 31.2 points apart on average over 3 shared benchmarks.
- Widest single gap
- FrontierMath, tier 4: DeepSeek V4 Pro 0813 26.8% against GPT-6.1 Terra 92.7%, 65.9 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Pro 0813 $1.98 against GPT-6.1 Terra $5.00 per million output tokens, 2.5x apart.
- Context window
- DeepSeek V4 Pro 0813 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 Pro 0813 | Bars | GPT-6.1 Terra | Ties |
|---|---|---|---|---|
| Coding | 0 | 7 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 3 | 1 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 3 | 18 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index07
| Benchmark | DeepSeek V4 Pro 0813 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 94.3% | Only GPT-6.1 Terra measured |
| LMArena WebDev | 1582 | 1673 | GPT-6.1 Terra |
| AA Coding Index | 68.8 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LiveCodeBench (Vals AI) | 87.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SWE-bench Verified (Vals AI) | 96.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Terminal-Bench 4 (Vals AI) | 14.1% | 49.5% | GPT-6.1 Terra |
| Vibe Code Bench (Vals AI) | 82.3% | 84.0% | GPT-6.1 Terra |
| Code migration (Vals AI) | 41.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| IOI (Vals AI) | 51.6% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Terminal-Bench 2.1 (Vals AI) | 54.7% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Vibe Code Bench 1-100 (Vals AI) | 17.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SkillsBench (Vals AI) | 53.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| CyberBench (Vals AI) | 72.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SciCode | 51.0% | 55.1% | GPT-6.1 Terra |
| FrontierCode | 28.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| WeirdML | 66.2% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ALE-Bench | 1403.2 | 2608.8 | GPT-6.1 Terra |
| LMArena Text: coding | 1469 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: software and IT | 1461 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena WebDev: React | 1588 | 1657 | GPT-6.1 Terra |
| LMArena WebDev: HTML | 1565 | 1719 | GPT-6.1 Terra |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V4 Pro 0813 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.1 | 51.0 | GPT-6.1 Terra |
| Epoch Capabilities Index | 155.6 | Not measured | Only DeepSeek V4 Pro 0813 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | DeepSeek V4 Pro 0813 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| AA Agentic Index | 41.3 | Not measured | Only DeepSeek V4 Pro 0813 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 |
| SREBench (Vals AI) | 1.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Finance Agent (Vals AI) | 50.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Tax Agent Bench (Vals AI) | 26.8% | 15.2% | DeepSeek V4 Pro 0813 |
| Legal Research Bench (Vals AI) | 40.9% | 26.0% | DeepSeek V4 Pro 0813 |
| Harvey's Legal Agent Benchmark (Vals AI) | 10.8% | 1.7% | DeepSeek V4 Pro 0813 |
| Excel Modeling Benchmark (Vals AI) | 52.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| APEX-Agents | 47.3% | 68.3% | GPT-6.1 Terra |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V4 Pro 0813 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| GPQA Diamond | 92.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LiveBench reasoning | Not measured | 88.7% | Only GPT-6.1 Terra measured |
| GPQA Diamond (Artificial Analysis run) | 92.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Humanity's Last Exam (Artificial Analysis run) | 41.0% | 46.2% | GPT-6.1 Terra |
| GPQA Diamond (Epoch AI run) | 91.7% | 94.3% | GPT-6.1 Terra |
| ARC-AGI | 90.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ARC-AGI-2 | 61.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Chess puzzles | 46.0% | Not measured | Only DeepSeek V4 Pro 0813 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 | 1458 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: expert | 1459 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: hard prompts in English | 1463 | Not measured | Only DeepSeek V4 Pro 0813 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 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V4 Pro 0813 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.6% | 100.0% | GPT-6.1 Terra |
| FrontierMath, tiers 1 to 3 | 64.6% | 90.9% | GPT-6.1 Terra |
| FrontierMath, tier 4 | 26.8% | 92.7% | GPT-6.1 Terra |
| ProofBench | 50.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: math | 1442 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: mathematical work | 1443 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V4 Pro 0813 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| MMLU Pro | 87.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LegalBench (Vals AI) | 82.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| CorpFin (Vals AI) | 65.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| TaxEval (Vals AI) | 73.1% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| MedCode (Vals AI) | 42.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SimpleQA Verified | 52.9% | 57.3% | GPT-6.1 Terra |
| LMArena Text: science | 1458 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: medicine and healthcare | 1446 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: legal and government | 1459 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: business and finance | 1442 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | DeepSeek V4 Pro 0813 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1283 | Only GPT-6.1 Terra measured |
| Design Arena: UI components | Not measured | 1277 | Only GPT-6.1 Terra measured |
| Design Arena: game dev | Not measured | 1348 | Only GPT-6.1 Terra measured |
| Design Arena: all code categories | Not measured | 1295 | Only GPT-6.1 Terra measured |
| LiveBench design | Not measured | 82.3% | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 4 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V4 Pro 0813 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Vals Index | 53.0% | 60.5% | GPT-6.1 Terra |
| LiveBench data analysis | Not measured | 82.3% | Only GPT-6.1 Terra measured |
| MedScribe (Vals AI) | 80.2% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Long context reasoning (AA-LCR) | 80.3% | 82.7% | GPT-6.1 Terra |
| DTBench | 93.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMCA | 45.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Furniture assembly | Not measured | 79.2% | Only GPT-6.1 Terra measured |
| LMArena Text | 1446 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: instruction following | 1449 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: creative writing | 1440 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: English | 1458 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: non-English | 1431 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: Chinese | 1482 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: Korean | 1447 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: French | 1447 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: Spanish | 1435 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: Russian | 1447 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: multi-turn | 1454 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: longer queries | 1458 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: writing and language | 1444 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: entertainment and media | 1424 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| MultiChallenge | Not measured | 74.2% | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Pro 0813 | 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 Pro 0813 costs less
Repository review
50K input + 3K output tokens
DeepSeek V4 Pro 0813 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4 Pro 0813 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 Pro 0813 | OpenAI GPT-6.1 Terra |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | August 12, 2026 | October 26, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.66 | $1.00 |
| Output $/Mtok | $1.98 | $5.00 |
| Coding index | 56.1 | 77.4 |
| Independent measurements behind it | 5 | 4 |
| Cost per solved task | $0.10 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Pro 0813 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 56.1 for DeepSeek V4 Pro 0813, though on 4 benchmarks against 5. Pick DeepSeek V4 Pro 0813 for output tokens 2.5x cheaper ($1.98 vs $5.00 per million) and work measured by Tax Agent Bench (Vals AI) or Legal Research Bench (Vals AI), where it leads.
Which is cheaper, DeepSeek V4 Pro 0813 or GPT-6.1 Terra?
DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; GPT-6.1 Terra costs $1.00 and $5.00. Cost per solved task is known for DeepSeek V4 Pro 0813 only.
Which has the bigger context window, DeepSeek V4 Pro 0813 or GPT-6.1 Terra?
GPT-6.1 Terra, with 1.05M tokens against 1.05M.
How many benchmarks is the DeepSeek V4 Pro 0813 vs GPT-6.1 Terra comparison based on?
21 benchmarks have a result for both models as of October 29, 2026. DeepSeek V4 Pro 0813's coding index rests on 5 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.