GPT-5.6 Terra vs Qwen3.5 Plus 2026-04-20
GPT-5.6 Terra leads Qwen3.5 Plus 2026-04-20 on coding, 63.9 to 39.5 on the Vibe Coding Index, and Qwen3.5 Plus 2026-04-20 costs 6.7x less per output token ($1.80 vs $12.00 per million). Updated October 22, 2026; 20 benchmarks have a result for both.
GPT-5.6 Terra or Qwen3.5 Plus 2026-04-20: which to pick
Pick GPT-5.6 Terra for coding: it scores 63.9 on the Vibe Coding Index against 39.5 for Qwen3.5 Plus 2026-04-20.
Pick Qwen3.5 Plus 2026-04-20 for output tokens 6.7x cheaper ($1.80 vs $12.00 per million) and work measured by MMLU Pro, where it leads.
- Shared results
- 20
- GPT-5.6 Terra only
- 109
- Qwen3.5 Plus 2026-04-20 only
- 5
- 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-5.6 Terra
GPT-5.6 Terra scores 63.9 against 39.5.
6 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-5.6 Terra has a AA Intelligence Index result, 42.1.
Directional only
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
GPT-5.6 Terra
GPT-5.6 Terra leads, 90.9% against 87.4%.
Same board, both measured
Math
AIME
No call
Only Qwen3.5 Plus 2026-04-20 has a AIME result, 86.0%.
Directional only
Knowledge
MMLU Pro
Qwen3.5 Plus 2026-04-20
Qwen3.5 Plus 2026-04-20 leads, 87.2% against 86.7%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-5.6 Terra has a Design Arena: websites result, 1268.
Directional only
Long documents
Listed context window
GPT-5.6 Terra
GPT-5.6 Terra takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5 Plus 2026-04-20
GPT-5.6 Terra $0.0080, Qwen3.5 Plus 2026-04-20 $0.0012 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.6 Terra
GPT-5.6 Terra $0.42, Qwen3.5 Plus 2026-04-20 $1.35.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.6 Terra 63.9 from 6 benchmarks, Qwen3.5 Plus 2026-04-20 39.5 from 2 benchmarks.
- Widest category
- Agentic work, 45.9 points apart on average over 1 shared benchmark.
- Widest single gap
- MMMU Pro (Vals AI): GPT-5.6 Terra 86.5% against Qwen3.5 Plus 2026-04-20 22.8%, 63.7 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Terra $12.00 against Qwen3.5 Plus 2026-04-20 $1.80 per million output tokens, 6.7x apart.
- Context window
- GPT-5.6 Terra takes 1.05M tokens, Qwen3.5 Plus 2026-04-20 1M.
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 | GPT-5.6 Terra | Bars | Qwen3.5 Plus 2026-04-20 | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 1 | 0 | ||
| Knowledge | 3 | 1 | 1 tie | |
| General | 3 | 0 | ||
| All shared boards | 18 | 1 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | GPT-5.6 Terra | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| LiveBench coding | 86.2% | Not measured | Only GPT-5.6 Terra measured |
| LMArena WebDev | 1522 | Not measured | Only GPT-5.6 Terra measured |
| AA Coding Index | 76.7 | Not measured | Only GPT-5.6 Terra measured |
| LiveCodeBench (Vals AI) | 85.9% | 85.3% | GPT-5.6 Terra |
| SWE-bench Verified (Vals AI) | 95.4% | 71.2% | GPT-5.6 Terra |
| Terminal-Bench 4 (Vals AI) | 22.7% | Not measured | Only GPT-5.6 Terra measured |
| Vibe Code Bench (Vals AI) | 74.6% | 15.7% | GPT-5.6 Terra |
| Code migration (Vals AI) | 47.8% | Not measured | Only GPT-5.6 Terra measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-5.6 Terra measured |
| IOI (Vals AI) | 87.6% | Not measured | Only GPT-5.6 Terra measured |
| Terminal-Bench 2.1 (Vals AI) | 77.5% | Not measured | Only GPT-5.6 Terra measured |
| Vibe Code Bench 1-100 (Vals AI) | 14.8% | Not measured | Only GPT-5.6 Terra measured |
| SkillsBench (Vals AI) | 58.9% | Not measured | Only GPT-5.6 Terra measured |
| CyberBench (Vals AI) | 72.1% | Not measured | Only GPT-5.6 Terra measured |
| SciCode | 55.0% | Not measured | Only GPT-5.6 Terra measured |
| Terminal-Bench Hard (Artificial Analysis run) | 62.9% | Not measured | Only GPT-5.6 Terra measured |
| FrontierCode | 41.3% | Not measured | Only GPT-5.6 Terra measured |
| WeirdML | 78.3% | Not measured | Only GPT-5.6 Terra measured |
| ALE-Bench | 1951.4 | 608.9 | GPT-5.6 Terra |
| LMArena Text: coding | 1485 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: software and IT | 1482 | Not measured | Only GPT-5.6 Terra measured |
| LMArena WebDev: React | 1513 | Not measured | Only GPT-5.6 Terra measured |
| LMArena WebDev: HTML | 1526 | Not measured | Only GPT-5.6 Terra measured |
| LMArena WebDev: from an image | 1541 | Not measured | Only GPT-5.6 Terra measured |
| SciCode | 10.8% | Not measured | Only GPT-5.6 Terra measured |
| SWE-Bench Pro V2 | 92.4% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.6 Terra | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| AA Intelligence Index | 42.1 | Not measured | Only GPT-5.6 Terra measured |
| Epoch Capabilities Index | 160.1 | 146.2 | GPT-5.6 Terra |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.6 Terra | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| AA Agentic Index | 43.2 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building web apps | 1120 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building full-stack apps | 1061 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building mobile apps | 1110 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building Android apps | 1060 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: agents building games | 1083 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: HTML slides | 1047 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: PowerPoint slides | 1104 | Not measured | Only GPT-5.6 Terra measured |
| LiveBench research | 60.4% | Not measured | Only GPT-5.6 Terra measured |
| LiveBench browser | 84.0% | Not measured | Only GPT-5.6 Terra measured |
| LiveBench long agentic | 48.4% | Not measured | Only GPT-5.6 Terra measured |
| SREBench (Vals AI) | 9.5% | Not measured | Only GPT-5.6 Terra measured |
| Finance Agent (Vals AI) | 54.4% | Not measured | Only GPT-5.6 Terra measured |
| Tax Agent Bench (Vals AI) | 30.0% | Not measured | Only GPT-5.6 Terra measured |
| Legal Research Bench (Vals AI) | 41.4% | Not measured | Only GPT-5.6 Terra measured |
| Excel Modeling Benchmark (Vals AI) | 66.2% | Not measured | Only GPT-5.6 Terra measured |
| Terminal-Bench-Science (Vals AI) | 10.0% | Not measured | Only GPT-5.6 Terra measured |
| τ²-Bench Telecom | 86.3% | Not measured | Only GPT-5.6 Terra measured |
| APEX-Agents | 58.2% | Not measured | Only GPT-5.6 Terra measured |
| BALROG | 53.2% | Not measured | Only GPT-5.6 Terra measured |
| Vending-Bench 2 | $7,343 | $1 | GPT-5.6 Terra |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5.6 Terra | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| GPQA Diamond | 90.9% | 87.4% | GPT-5.6 Terra |
| LiveBench reasoning | 90.6% | Not measured | Only GPT-5.6 Terra measured |
| MMMU Pro (Vals AI) | 86.5% | 22.8% | GPT-5.6 Terra |
| GPQA Diamond (Artificial Analysis run) | 92.5% | Not measured | Only GPT-5.6 Terra measured |
| Humanity's Last Exam (Artificial Analysis run) | 42.9% | Not measured | Only GPT-5.6 Terra measured |
| GPQA Diamond (Epoch AI run) | 93.3% | 84.8% | GPT-5.6 Terra |
| ARC-AGI | 96.5% | Not measured | Only GPT-5.6 Terra measured |
| ARC-AGI-2 | 83.9% | Not measured | Only GPT-5.6 Terra measured |
| SimpleBench | 48.9% | Not measured | Only GPT-5.6 Terra measured |
| Chess puzzles | 47.0% | 8.0% | GPT-5.6 Terra |
| Mystery game puzzles | 35.0% | 17.0% | GPT-5.6 Terra |
| LMArena Text: hard prompts | 1469 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: expert | 1496 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: hard prompts in English | 1465 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: diagrams | 1295 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: homework | 1312 | Not measured | Only GPT-5.6 Terra measured |
| Kagi LLM Benchmark | 51.3% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.6 Terra | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| AIME | Not measured | 86.0% | Only Qwen3.5 Plus 2026-04-20 measured |
| OTIS Mock AIME | 99.7% | 86.7% | GPT-5.6 Terra |
| FrontierMath, tiers 1 to 3 | 86.0% | Not measured | Only GPT-5.6 Terra measured |
| FrontierMath, tier 4 | 70.7% | Not measured | Only GPT-5.6 Terra measured |
| ProofBench | 74.0% | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: math | 1465 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: mathematical work | 1478 | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | GPT-5.6 Terra | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| MMLU Pro | 86.7% | 87.2% | Qwen3.5 Plus 2026-04-20 |
| LegalBench (Vals AI) | 85.1% | 85.1% | GPT-5.6 Terra |
| CaseLaw (Vals AI) | Not measured | 59.7% | Only Qwen3.5 Plus 2026-04-20 measured |
| CorpFin (Vals AI) | 65.3% | 65.3% | Tie |
| TaxEval (Vals AI) | 76.2% | Not measured | Only GPT-5.6 Terra measured |
| MortgageTax (Vals AI) | 67.3% | 60.8% | GPT-5.6 Terra |
| MedQA (Vals AI) | Not measured | 95.2% | Only Qwen3.5 Plus 2026-04-20 measured |
| MedCode (Vals AI) | 43.4% | Not measured | Only GPT-5.6 Terra measured |
| SimpleQA Verified | 43.2% | 25.4% | GPT-5.6 Terra |
| LMArena Text: science | 1452 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: medicine and healthcare | 1430 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: legal and government | 1461 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: business and finance | 1448 | Not measured | Only GPT-5.6 Terra measured |
| FACTS Benchmark Suite | 52.0% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-5.6 Terra | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| Design Arena: websites | 1268 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: UI components | 1256 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: game dev | 1229 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: data viz | 1240 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: 3D | 1134 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: all code categories | 1240 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: SVG | 1219 | Not measured | Only GPT-5.6 Terra measured |
| Design Arena: ASCII art | 1178 | Not measured | Only GPT-5.6 Terra measured |
| LiveBench design | 76.0% | Not measured | Only GPT-5.6 Terra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5.6 Terra | Qwen3.5 Plus 2026-04-20 | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | Not measured | Only GPT-5.6 Terra measured |
| Public Benefits Bench (Vals AI) | 62.4% | Not measured | Only GPT-5.6 Terra measured |
| SAGE (Vals AI) | 47.0% | 30.4% | GPT-5.6 Terra |
| MedScribe (Vals AI) | 82.9% | Not measured | Only GPT-5.6 Terra measured |
| Vals Multimodal Index | 65.1% | Not measured | Only GPT-5.6 Terra measured |
| IFBench | 71.2% | Not measured | Only GPT-5.6 Terra measured |
| Long context reasoning (AA-LCR) | 83.0% | Not measured | Only GPT-5.6 Terra measured |
| DTBench | 93.3% | 80.5% | GPT-5.6 Terra |
| LMCA | 54.9% | 36.4% | GPT-5.6 Terra |
| CL-bench | Not measured | 19.8% | Only Qwen3.5 Plus 2026-04-20 measured |
| Surface Evolver Bench | 83.8% | Not measured | Only GPT-5.6 Terra measured |
| Furniture assembly | 54.2% | Not measured | Only GPT-5.6 Terra measured |
| CL-bench Life | Not measured | 12.4% | Only Qwen3.5 Plus 2026-04-20 measured |
| LMArena Text | 1448 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: instruction following | 1456 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: creative writing | 1413 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision | 1271 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: English | 1449 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: non-English | 1441 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Chinese | 1514 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: German | 1460 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Japanese | 1454 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Korean | 1427 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: French | 1466 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Spanish | 1451 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Russian | 1452 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Polish | 1446 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: multi-turn | 1453 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: longer queries | 1454 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: writing and language | 1431 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: entertainment and media | 1418 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: English | 1272 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: Chinese | 1337 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: reading text | 1278 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: humor | 1236 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: creative writing | 1248 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Document | 1472 | Not measured | Only GPT-5.6 Terra measured |
| EQ-Bench 4 | 1234 | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Terra | Qwen3.5 Plus 2026-04-20 | 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
Qwen3.5 Plus 2026-04-20 costs less
Repository review
50K input + 3K output tokens
Qwen3.5 Plus 2026-04-20 costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 Plus 2026-04-20 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 | OpenAI GPT-5.6 Terra | Qwen3.5 Plus 2026-04-20 |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | July 9, 2026 | April 27, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $2.00 | $0.30 |
| Output $/Mtok | $12.00 | $1.80 |
| Coding index | 63.9 | 39.5 |
| Independent measurements behind it | 6 | 2 |
| Cost per solved task | $0.42 | $1.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Terra better than Qwen3.5 Plus 2026-04-20 for coding?
Pick GPT-5.6 Terra for coding: it scores 63.9 on the Vibe Coding Index against 39.5 for Qwen3.5 Plus 2026-04-20. Pick Qwen3.5 Plus 2026-04-20 for output tokens 6.7x cheaper ($1.80 vs $12.00 per million) and work measured by MMLU Pro, where it leads.
Which is cheaper, GPT-5.6 Terra or Qwen3.5 Plus 2026-04-20?
GPT-5.6 Terra costs $2.00 per million input tokens and $12.00 per million output tokens; Qwen3.5 Plus 2026-04-20 costs $0.30 and $1.80. Per solved SWE-bench Verified task, GPT-5.6 Terra costs $0.42 and Qwen3.5 Plus 2026-04-20 $1.35.
Which has the bigger context window, GPT-5.6 Terra or Qwen3.5 Plus 2026-04-20?
GPT-5.6 Terra, with 1.05M tokens against 1M.
How many benchmarks is the GPT-5.6 Terra vs Qwen3.5 Plus 2026-04-20 comparison based on?
20 benchmarks have a result for both models as of October 22, 2026. GPT-5.6 Terra's coding index rests on 6 independent benchmarks and Qwen3.5 Plus 2026-04-20's on 2. Where only one model has a result, the page says so instead of naming a winner.