GLM 5V Turbo vs GPT-6.1 Sol
Updated October 21, 2026. 44 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 44 shared
Decision reading
Pick GPT-6.1 Sol for coding: it scores 88.7 on the Vibe Coding Index against 28.8 for GLM 5V Turbo.
Pick GLM 5V Turbo when output tokens cost 2.5x less, or when what matters is LMArena Text: science or LMArena Text: English, where it leads.
Model AGLM 5V TurboZ.ai28.8/1001 independent benchmarkNo cost per solved taskModel BGPT-6.1 SolOpenAI88.7/1002 independent benchmarksNo cost per solved task
- Shared results
- 44
- GLM 5V Turbo only
- 21
- GPT-6.1 Sol only
- 51
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
GPT-6.1 Sol
GPT-6.1 Sol scores 88.7 against 28.8.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6.1 Sol
GPT-6.1 Sol leads, 51.8 against 23.5.
Same board, both measured
Web design
Design Arena: websites
GPT-6.1 Sol
GPT-6.1 Sol leads, 1321 against 1230.
Same board, both measured
General
Vals Index
No call
Only GPT-6.1 Sol has a Vals Index result, 63.9%.
Directional only
Long documents
Listed context window
GPT-6.1 Sol
GPT-6.1 Sol takes 1.05M tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5V Turbo
GLM 5V Turbo $0.0032, GPT-6.1 Sol $0.0070 per turn.
List prices
At a glance
- Coding index
- GLM 5V Turbo 28.8 from 1 benchmark, GPT-6.1 Sol 88.7 from 2 benchmarks.
- Widest category
- Intelligence, 28.3 points apart on average over 1 shared benchmark.
- Widest single gap
- LMArena WebDev: GLM 5V Turbo 1402 against GPT-6.1 Sol 1753, 50.2 points apart on a 0 to 100 scale.
- Output price
- GLM 5V Turbo $4.00 against GPT-6.1 Sol $10.00 per million output tokens, 2.5x apart.
- Context window
- GLM 5V Turbo takes 203K tokens, GPT-6.1 Sol 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 | GLM 5V Turbo | Bars | GPT-6.1 Sol | Ties |
|---|---|---|---|---|
| Coding | 0 | 6 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 2 | ||
| Knowledge | 1 | 3 | ||
| Web design | 0 | 6 | ||
| General | 4 | 14 | ||
| All shared boards | 5 | 39 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index06
| Benchmark | GLM 5V Turbo | GPT-6.1 Sol | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 96.0% | Only GPT-6.1 Sol measured |
| LMArena WebDev | 1402 | 1753 | GPT-6.1 Sol |
| Terminal-Bench 4 (Vals AI) | Not measured | 55.0% | Only GPT-6.1 Sol measured |
| Vibe Code Bench (Vals AI) | Not measured | 88.9% | Only GPT-6.1 Sol measured |
| Code migration (Vals AI) | Not measured | 65.1% | Only GPT-6.1 Sol measured |
| ProgramBench (Vals AI) | Not measured | 3.0% | Only GPT-6.1 Sol measured |
| IOI (Vals AI) | Not measured | 96.9% | Only GPT-6.1 Sol measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 43.5% | Only GPT-6.1 Sol measured |
| CyberBench (Vals AI) | Not measured | 39.3% | Only GPT-6.1 Sol measured |
| SciCode | Not measured | 55.8% | Only GPT-6.1 Sol measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | Not measured | Only GLM 5V Turbo measured |
| FrontierCode | Not measured | 50.2% | Only GPT-6.1 Sol measured |
| ALE-Bench | Not measured | 2743.8 | Only GPT-6.1 Sol measured |
| LMArena Text: coding | 1466 | 1478 | GPT-6.1 Sol |
| LMArena Text: software and IT | 1460 | 1476 | GPT-6.1 Sol |
| LMArena WebDev: React | 1386 | 1754 | GPT-6.1 Sol |
| LMArena WebDev: HTML | 1356 | 1800 | GPT-6.1 Sol |
| LMArena WebDev: from an image | 1425 | 1702 | GPT-6.1 Sol |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 5V Turbo | GPT-6.1 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | 51.8 | GPT-6.1 Sol |
| Epoch Capabilities Index | Not measured | 168.4 | Only GPT-6.1 Sol measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 5V Turbo | GPT-6.1 Sol | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1124 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building full-stack apps | 1149 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building mobile apps | 1134 | 1190 | GPT-6.1 Sol |
| Design Arena: agents building Android apps | 1267 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building Godot games | 957 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building games | 1102 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: HTML slides | 1120 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | 1152 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: spreadsheets | Not measured | 1250 | Only GPT-6.1 Sol measured |
| LiveBench research | Not measured | 83.5% | Only GPT-6.1 Sol measured |
| LiveBench browser | Not measured | 88.0% | Only GPT-6.1 Sol measured |
| LiveBench long agentic | Not measured | 73.0% | Only GPT-6.1 Sol measured |
| SREBench (Vals AI) | Not measured | 50.8% | Only GPT-6.1 Sol measured |
| Finance Agent (Vals AI) | Not measured | 52.0% | Only GPT-6.1 Sol measured |
| Tax Agent Bench (Vals AI) | Not measured | 21.8% | Only GPT-6.1 Sol measured |
| Legal Research Bench (Vals AI) | Not measured | 38.5% | Only GPT-6.1 Sol measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 6.3% | Only GPT-6.1 Sol measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 70.8% | Only GPT-6.1 Sol measured |
| BioMysteryBench (Vals AI) | Not measured | 79.6% | Only GPT-6.1 Sol measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 52.9% | Only GPT-6.1 Sol measured |
| Vals Science Index | Not measured | 59.6% | Only GPT-6.1 Sol measured |
| Robo-bench (Vals AI) | Not measured | 28.3% | Only GPT-6.1 Sol measured |
| τ²-Bench Telecom | 98.5% | Not measured | Only GLM 5V Turbo measured |
| APEX-Agents | Not measured | 60.0% | Only GPT-6.1 Sol measured |
| SpireClimb | Not measured | 24.7% | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 14 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GLM 5V Turbo | GPT-6.1 Sol | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 92.6% | Only GPT-6.1 Sol measured |
| MysteryMechanism (Vals AI) | Not measured | 46.4% | Only GPT-6.1 Sol measured |
| GPQA Diamond (Artificial Analysis run) | 80.9% | Not measured | Only GLM 5V Turbo measured |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 52.9% | GPT-6.1 Sol |
| GPQA Diamond (Epoch AI run) | Not measured | 95.4% | Only GPT-6.1 Sol measured |
| ARC-AGI | Not measured | 98.5% | Only GPT-6.1 Sol measured |
| ARC-AGI-2 | Not measured | 94.2% | Only GPT-6.1 Sol measured |
| Chess puzzles | Not measured | 68.0% | Only GPT-6.1 Sol measured |
| Mystery game puzzles | Not measured | 80.0% | Only GPT-6.1 Sol measured |
| EBR-bench | Not measured | 54.3% | Only GPT-6.1 Sol measured |
| LMArena Text: hard prompts | 1443 | 1463 | GPT-6.1 Sol |
| LMArena Text: expert | 1453 | 1489 | GPT-6.1 Sol |
| LMArena Text: hard prompts in English | 1456 | 1465 | GPT-6.1 Sol |
| LMArena Vision: diagrams | 1286 | 1306 | GPT-6.1 Sol |
| LMArena Vision: homework | 1273 | 1356 | GPT-6.1 Sol |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 5V Turbo | GPT-6.1 Sol | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 100.0% | Only GPT-6.1 Sol measured |
| FrontierMath, tiers 1 to 3 | Not measured | 93.7% | Only GPT-6.1 Sol measured |
| FrontierMath, tier 4 | Not measured | 100.0% | Only GPT-6.1 Sol measured |
| ProofBench | Not measured | 99.0% | Only GPT-6.1 Sol measured |
| LMArena Text: math | 1442 | 1489 | GPT-6.1 Sol |
| LMArena Text: mathematical work | 1447 | 1513 | GPT-6.1 Sol |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | GLM 5V Turbo | GPT-6.1 Sol | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 48.8% | Only GPT-6.1 Sol measured |
| SimpleQA Verified | Not measured | 73.9% | Only GPT-6.1 Sol measured |
| LMArena Text: science | 1448 | 1444 | GLM 5V Turbo |
| LMArena Text: medicine and healthcare | 1433 | 1433 | GPT-6.1 Sol |
| LMArena Text: legal and government | 1436 | 1471 | GPT-6.1 Sol |
| LMArena Text: business and finance | 1435 | 1445 | GPT-6.1 Sol |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GLM 5V Turbo | GPT-6.1 Sol | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | 1321 | GPT-6.1 Sol |
| Design Arena: UI components | 1213 | 1321 | GPT-6.1 Sol |
| Design Arena: game dev | 1219 | 1389 | GPT-6.1 Sol |
| Design Arena: data viz | 1202 | 1278 | GPT-6.1 Sol |
| Design Arena: 3D | 1209 | 1461 | GPT-6.1 Sol |
| Design Arena: all code categories | 1228 | 1345 | GPT-6.1 Sol |
| Design Arena: SVG | 1151 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: ASCII art | 1118 | Not measured | Only GLM 5V Turbo measured |
| LiveBench design | Not measured | 82.1% | Only GPT-6.1 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index414
| Benchmark | GLM 5V Turbo | GPT-6.1 Sol | Leader |
|---|---|---|---|
| Vals Index | Not measured | 63.9% | Only GPT-6.1 Sol measured |
| LiveBench data analysis | Not measured | 82.7% | Only GPT-6.1 Sol measured |
| Public Benefits Bench (Vals AI) | Not measured | 59.3% | Only GPT-6.1 Sol measured |
| SAGE (Vals AI) | Not measured | 46.5% | Only GPT-6.1 Sol measured |
| MedScribe (Vals AI) | Not measured | 86.5% | Only GPT-6.1 Sol measured |
| IFBench | 61.1% | Not measured | Only GLM 5V Turbo measured |
| Long context reasoning (AA-LCR) | 70.3% | 84.0% | GPT-6.1 Sol |
| DTBench | Not measured | 96.5% | Only GPT-6.1 Sol measured |
| LMCA | Not measured | 62.8% | Only GPT-6.1 Sol measured |
| Furniture assembly | Not measured | 80.0% | Only GPT-6.1 Sol measured |
| LMArena Text | 1437 | 1443 | GPT-6.1 Sol |
| LMArena Text: instruction following | 1423 | 1466 | GPT-6.1 Sol |
| LMArena Text: creative writing | 1417 | 1425 | GPT-6.1 Sol |
| LMArena Vision | 1264 | 1288 | GPT-6.1 Sol |
| LMArena Text: English | 1454 | 1450 | GLM 5V Turbo |
| LMArena Text: non-English | 1420 | 1433 | GPT-6.1 Sol |
| LMArena Text: Chinese | 1491 | 1487 | GLM 5V Turbo |
| LMArena Text: German | 1422 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Korean | 1397 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: French | 1443 | 1460 | GPT-6.1 Sol |
| LMArena Text: Spanish | 1452 | 1439 | GLM 5V Turbo |
| LMArena Text: Russian | 1432 | 1457 | GPT-6.1 Sol |
| LMArena Text: Polish | 1432 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: multi-turn | 1431 | 1442 | GPT-6.1 Sol |
| LMArena Text: longer queries | 1438 | 1458 | GPT-6.1 Sol |
| LMArena Text: writing and language | 1420 | 1444 | GPT-6.1 Sol |
| LMArena Text: entertainment and media | 1407 | 1426 | GPT-6.1 Sol |
| LMArena Vision: English | 1274 | 1274 | GLM 5V Turbo |
| LMArena Vision: Chinese | 1329 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: reading text | 1270 | 1289 | GPT-6.1 Sol |
| LMArena Vision: humor | 1268 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: captioning | 1264 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: recognizing things | 1241 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: creative writing | 1252 | 1301 | GPT-6.1 Sol |
| LMArena Document | 1416 | Not measured | Only GLM 5V Turbo 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 | GLM 5V Turbo | GPT-6.1 Sol | 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
GLM 5V Turbo$0.0032Fits in one request
GPT-6.1 Sol$0.0070Fits in one request
GLM 5V Turbo costs less
Repository review
50K input + 3K output tokens
GLM 5V Turbo$0.072Fits in one request
GPT-6.1 Sol$0.130Fits in one request
GLM 5V Turbo costs less
Agent loop
200K input + 10K output tokens
GLM 5V Turbo$0.280Exceeds the context window
GPT-6.1 Sol$0.500Fits in one request
GLM 5V Turbo 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 | Z.ai GLM 5V Turbo | OpenAI GPT-6.1 Sol |
|---|---|---|
| Maker | Z.ai | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | April 1, 2026 | September 29, 2026 |
| Context window | 203K | 1.05M |
| Input $/Mtok | $1.20 | $2.00 |
| Output $/Mtok | $4.00 | $10.00 |
| Coding index | 28.8 | 88.7 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5V Turbo better than GPT-6.1 Sol for coding?
Pick GPT-6.1 Sol for coding: it scores 88.7 on the Vibe Coding Index against 28.8 for GLM 5V Turbo. Pick GLM 5V Turbo when output tokens cost 2.5x less, or when what matters is LMArena Text: science or LMArena Text: English, where it leads.
Which is cheaper, GLM 5V Turbo or GPT-6.1 Sol?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; GPT-6.1 Sol costs $2.00 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5V Turbo or GPT-6.1 Sol?
GPT-6.1 Sol, with 1.05M tokens against 203K.
How many benchmarks is the GLM 5V Turbo vs GPT-6.1 Sol comparison based on?
44 benchmarks have a result for both models as of October 21, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and GPT-6.1 Sol's on 2. Where only one model has a result, the page says so instead of naming a winner.