GLM 5V Turbo vs GPT-5.1-Codex-Max
GLM 5V Turbo costs 2.5x less per output token than GPT-5.1-Codex-Max ($4.00 vs $10.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $4.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $10.00
GLM 5V Turbo or GPT-5.1-Codex-Max: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 5V Turbo for output tokens 2.5x cheaper ($4.00 vs $10.00 per million).
No benchmark has tested both yet. GLM 5V Turbo has results on LMArena WebDev, Terminal-Bench Hard (Artificial Analysis run) and LMArena Text: coding; GPT-5.1-Codex-Max on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench. Compare them on price and context instead.
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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GLM 5V Turbo has a AA Intelligence Index result, 23.5.
Directional only
Web design
Design Arena: websites
No call
Only GLM 5V Turbo has a Design Arena: websites result, 1230.
Directional only
Long documents
Listed context window
GPT-5.1-Codex-Max
GPT-5.1-Codex-Max takes 400K tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5V Turbo
GLM 5V Turbo $0.0032, GPT-5.1-Codex-Max $0.0063 per turn.
List prices
At a glance
- Coding index
- GLM 5V Turbo not benchmarked, GPT-5.1-Codex-Max not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GLM 5V Turbo $4.00 against GPT-5.1-Codex-Max $10.00 per million output tokens, 2.5x apart.
- Context window
- GLM 5V Turbo takes 203K tokens, GPT-5.1-Codex-Max 400K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index11 boards measured
| Benchmark | GLM 5V Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| LMArena WebDev | 1402 | Not measured | Only GLM 5V Turbo measured |
| LiveCodeBench (Vals AI) | Not measured | 83.6% | Only GPT-5.1-Codex-Max measured |
| Vibe Code Bench (Vals AI) | Not measured | 22.2% | Only GPT-5.1-Codex-Max measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | Not measured | Only GLM 5V Turbo measured |
| Terminal-Bench | Not measured | 60.4% | Only GPT-5.1-Codex-Max measured |
| ALE-Bench | Not measured | 1228.3 | Only GPT-5.1-Codex-Max measured |
| LMArena Text: coding | 1466 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: software and IT | 1460 | Not measured | Only GLM 5V Turbo measured |
| LMArena WebDev: React | 1386 | Not measured | Only GLM 5V Turbo measured |
| LMArena WebDev: HTML | 1356 | Not measured | Only GLM 5V Turbo measured |
| LMArena WebDev: from an image | 1425 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GLM 5V Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards measured
| Benchmark | GLM 5V Turbo | GPT-5.1-Codex-Max | 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 | Not measured | Only GLM 5V Turbo measured |
| 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 |
| τ²-Bench Telecom | 98.5% | Not measured | Only GLM 5V Turbo measured |
| METR time horizons | Not measured | 70.8% | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | GLM 5V Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 80.9% | Not measured | Only GLM 5V Turbo measured |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: hard prompts | 1443 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: expert | 1453 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: hard prompts in English | 1456 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: diagrams | 1286 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: homework | 1273 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GLM 5V Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| ProofBench | Not measured | 9.0% | Only GPT-5.1-Codex-Max measured |
| LMArena Text: math | 1442 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: mathematical work | 1447 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | GLM 5V Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| LMArena Text: science | 1448 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: medicine and healthcare | 1433 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: legal and government | 1436 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: business and finance | 1435 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 14 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | GLM 5V Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: UI components | 1213 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: game dev | 1219 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: data viz | 1202 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: 3D | 1209 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: all code categories | 1228 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: SVG | 1151 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: ASCII art | 1117 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index27 boards measured
| Benchmark | GLM 5V Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| IFBench | 61.1% | Not measured | Only GLM 5V Turbo measured |
| Long context reasoning (AA-LCR) | 70.3% | Not measured | Only GLM 5V Turbo measured |
| LMArena Text | 1437 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: instruction following | 1423 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: creative writing | 1417 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision | 1264 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: English | 1454 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: non-English | 1420 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Chinese | 1491 | Not measured | Only GLM 5V Turbo measured |
| 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 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Spanish | 1452 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Russian | 1432 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Polish | 1432 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: multi-turn | 1431 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: longer queries | 1438 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: writing and language | 1420 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: entertainment and media | 1407 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: English | 1274 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: Chinese | 1329 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: reading text | 1270 | Not measured | Only GLM 5V Turbo measured |
| 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 | Not measured | Only GLM 5V Turbo measured |
| LMArena Document | 1416 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 19 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 costs less
Repository review
50K input + 3K output tokens
GLM 5V Turbo costs less
Agent loop
200K input + 10K output tokens
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-5.1-Codex-Max |
|---|---|---|
| Maker | Z.ai | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | April 1, 2026 | December 4, 2025 |
| Context window | 203K | 400K |
| Input $/Mtok | $1.20 | $1.25 |
| Output $/Mtok | $4.00 | $10.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5V Turbo better than GPT-5.1-Codex-Max for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5V Turbo for output tokens 2.5x cheaper ($4.00 vs $10.00 per million).
Which is cheaper, GLM 5V Turbo or GPT-5.1-Codex-Max?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; GPT-5.1-Codex-Max costs $1.25 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5V Turbo or GPT-5.1-Codex-Max?
GPT-5.1-Codex-Max, with 400K tokens against 203K.
Has any benchmark tested both GLM 5V Turbo and GPT-5.1-Codex-Max?
No benchmark has tested both yet. GLM 5V Turbo has results on LMArena WebDev, Terminal-Bench Hard (Artificial Analysis run) and LMArena Text: coding; GPT-5.1-Codex-Max on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench. Compare them on price and context instead. Data as of October 21, 2026.