GPT-5.6 Terra vs Ling 3.0 Flash
GPT-5.6 Terra leads Ling 3.0 Flash on coding, 63.9 to 29.6 on the Vibe Coding Index, and Ling 3.0 Flash costs 98.8x less per output token ($0.1215 vs $12.00 per million). Updated October 22, 2026; 24 benchmarks have a result for both.
GPT-5.6 Terra or Ling 3.0 Flash: which to pick
Pick GPT-5.6 Terra for coding: it scores 63.9 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash.
Pick Ling 3.0 Flash for output tokens 98.8x cheaper ($0.1215 vs $12.00 per million) and a lower cost per solved task ($0.05 against $0.42).
- Shared results
- 24
- GPT-5.6 Terra only
- 105
- Ling 3.0 Flash only
- 0
- Like-for-like categories
- 6 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 29.6.
6 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Terra
GPT-5.6 Terra leads, 42.1 against 20.1.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.6 Terra
GPT-5.6 Terra leads, 43.2 against 19.3.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.6 Terra
GPT-5.6 Terra leads, 90.9% against 84.8%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.6 Terra
GPT-5.6 Terra leads, 86.7% against 82.0%.
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 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
GPT-5.6 Terra $0.0080, Ling 3.0 Flash $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Ling 3.0 Flash
GPT-5.6 Terra $0.42, Ling 3.0 Flash $0.05.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.6 Terra 63.9 from 6 benchmarks, Ling 3.0 Flash 29.6 from 2 benchmarks.
- Widest category
- Agentic work, 32.6 points apart on average over 4 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-5.6 Terra 74.6% against Ling 3.0 Flash 2.9%, 71.7 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Terra $12.00 against Ling 3.0 Flash $0.1215 per million output tokens, 98.8x apart.
- Context window
- GPT-5.6 Terra takes 1.05M tokens, Ling 3.0 Flash 262K.
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 | Ling 3.0 Flash | Ties |
|---|---|---|---|---|
| Coding | 8 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 4 | 0 | ||
| Reasoning | 3 | 0 | ||
| Knowledge | 5 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 24 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index80
| Benchmark | GPT-5.6 Terra | Ling 3.0 Flash | 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 | 50.6 | GPT-5.6 Terra |
| LiveCodeBench (Vals AI) | 85.9% | 84.0% | GPT-5.6 Terra |
| SWE-bench Verified (Vals AI) | 95.4% | 65.2% | 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% | 2.9% | GPT-5.6 Terra |
| Code migration (Vals AI) | 47.8% | 0.0% | GPT-5.6 Terra |
| 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% | 50.2% | GPT-5.6 Terra |
| Vibe Code Bench 1-100 (Vals AI) | 14.8% | Not measured | Only GPT-5.6 Terra measured |
| SkillsBench (Vals AI) | 58.9% | 27.9% | GPT-5.6 Terra |
| CyberBench (Vals AI) | 72.1% | Not measured | Only GPT-5.6 Terra measured |
| SciCode | 55.0% | 42.0% | GPT-5.6 Terra |
| 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 | Not measured | Only GPT-5.6 Terra measured |
| 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 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 42.1 | 20.1 | GPT-5.6 Terra |
| Epoch Capabilities Index | 160.1 | Not measured | Only GPT-5.6 Terra measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-5.6 Terra | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 43.2 | 19.3 | GPT-5.6 Terra |
| 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% | 30.3% | GPT-5.6 Terra |
| Tax Agent Bench (Vals AI) | 30.0% | Not measured | Only GPT-5.6 Terra measured |
| Legal Research Bench (Vals AI) | 41.4% | 0.0% | GPT-5.6 Terra |
| Excel Modeling Benchmark (Vals AI) | 66.2% | 25.0% | GPT-5.6 Terra |
| 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 | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5.6 Terra | Ling 3.0 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | 90.9% | 84.8% | GPT-5.6 Terra |
| LiveBench reasoning | 90.6% | Not measured | Only GPT-5.6 Terra measured |
| MMMU Pro (Vals AI) | 86.5% | Not measured | Only GPT-5.6 Terra measured |
| GPQA Diamond (Artificial Analysis run) | 92.5% | 85.5% | GPT-5.6 Terra |
| Humanity's Last Exam (Artificial Analysis run) | 42.9% | 23.7% | GPT-5.6 Terra |
| GPQA Diamond (Epoch AI run) | 93.3% | Not measured | Only GPT-5.6 Terra measured |
| 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% | Not measured | Only GPT-5.6 Terra measured |
| Mystery game puzzles | 35.0% | Not measured | Only GPT-5.6 Terra measured |
| 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 | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.6 Terra | Ling 3.0 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | 99.7% | Not measured | Only GPT-5.6 Terra measured |
| 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 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5.6 Terra | Ling 3.0 Flash | Leader |
|---|---|---|---|
| MMLU Pro | 86.7% | 82.0% | GPT-5.6 Terra |
| LegalBench (Vals AI) | 85.1% | 79.7% | GPT-5.6 Terra |
| CorpFin (Vals AI) | 65.3% | 61.9% | GPT-5.6 Terra |
| TaxEval (Vals AI) | 76.2% | 70.7% | GPT-5.6 Terra |
| MortgageTax (Vals AI) | 67.3% | Not measured | Only GPT-5.6 Terra measured |
| MedCode (Vals AI) | 43.4% | 32.3% | GPT-5.6 Terra |
| SimpleQA Verified | 43.2% | Not measured | Only GPT-5.6 Terra measured |
| 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 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-5.6 Terra | Ling 3.0 Flash | 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 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | Not measured | Only GPT-5.6 Terra measured |
| Public Benefits Bench (Vals AI) | 62.4% | 50.7% | GPT-5.6 Terra |
| SAGE (Vals AI) | 47.0% | Not measured | Only GPT-5.6 Terra measured |
| MedScribe (Vals AI) | 82.9% | 80.9% | GPT-5.6 Terra |
| 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% | 73.0% | GPT-5.6 Terra |
| DTBench | 93.3% | Not measured | Only GPT-5.6 Terra measured |
| LMCA | 54.9% | Not measured | Only GPT-5.6 Terra 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 |
| 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 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Terra | Ling 3.0 Flash | 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
Ling 3.0 Flash costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 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 | OpenAI GPT-5.6 Terra | inclusionAI Ling 3.0 Flash |
|---|---|---|
| Maker | OpenAI | inclusionAI |
| Weights | No public weights listed | Open weights |
| Released | July 9, 2026 | July 23, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $2.00 | $0.0405 |
| Output $/Mtok | $12.00 | $0.1215 |
| Coding index | 63.9 | 29.6 |
| Independent measurements behind it | 6 | 2 |
| Cost per solved task | $0.42 | $0.05 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Terra better than Ling 3.0 Flash for coding?
Pick GPT-5.6 Terra for coding: it scores 63.9 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash. Pick Ling 3.0 Flash for output tokens 98.8x cheaper ($0.1215 vs $12.00 per million) and a lower cost per solved task ($0.05 against $0.42).
Which is cheaper, GPT-5.6 Terra or Ling 3.0 Flash?
GPT-5.6 Terra costs $2.00 per million input tokens and $12.00 per million output tokens; Ling 3.0 Flash costs $0.0405 and $0.1215. Per solved SWE-bench Verified task, GPT-5.6 Terra costs $0.42 and Ling 3.0 Flash $0.05.
Which has the bigger context window, GPT-5.6 Terra or Ling 3.0 Flash?
GPT-5.6 Terra, with 1.05M tokens against 262K.
How many benchmarks is the GPT-5.6 Terra vs Ling 3.0 Flash comparison based on?
24 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 Ling 3.0 Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.