GLM 5 Turbo vs GPT-5.1-Codex-Max
GLM 5 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; 1 benchmarks have a result for both.
GLM 5 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 5 Turbo for output tokens 2.5x cheaper ($4.00 vs $10.00 per million) and work measured by ALE-Bench, where it leads.
- Shared results
- 1
- GLM 5 Turbo only
- 15
- GPT-5.1-Codex-Max only
- 5
- Like-for-like categories
- 1 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GLM 5 Turbo has a AA Intelligence Index result, 26.6.
Directional only
Web design
Design Arena: websites
No call
Only GLM 5 Turbo has a Design Arena: websites result, 1262.
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 5 Turbo
GLM 5 Turbo $0.0032, GPT-5.1-Codex-Max $0.0063 per turn.
List prices
At a glance
- Coding index
- GLM 5 Turbo not benchmarked, GPT-5.1-Codex-Max not benchmarked.
- Widest category
- Coding, 19.8 points apart on average over 1 shared benchmark.
- Widest single gap
- ALE-Bench: GLM 5 Turbo 634.0 against GPT-5.1-Codex-Max 1228.3, 19.8 points apart on a 0 to 100 scale.
- Output price
- GLM 5 Turbo $4.00 against GPT-5.1-Codex-Max $10.00 per million output tokens, 2.5x apart.
- Context window
- GLM 5 Turbo takes 203K tokens, GPT-5.1-Codex-Max 400K.
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 5 Turbo | Bars | GPT-5.1-Codex-Max | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GLM 5 Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| 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) | 33.3% | Not measured | Only GLM 5 Turbo measured |
| Terminal-Bench | Not measured | 60.4% | Only GPT-5.1-Codex-Max measured |
| ALE-Bench | 634.0 | 1228.3 | GPT-5.1-Codex-Max |
| Neither model has a result on the other 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GLM 5 Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| AA Intelligence Index | 26.6 | Not measured | Only GLM 5 Turbo measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GLM 5 Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 98.5% | Not measured | Only GLM 5 Turbo measured |
| METR time horizons | Not measured | 70.8% | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GLM 5 Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.7% | Not measured | Only GLM 5 Turbo measured |
| Humanity's Last Exam (Artificial Analysis run) | 27.8% | Not measured | Only GLM 5 Turbo measured |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GLM 5 Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| ProofBench | Not measured | 9.0% | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5 Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GLM 5 Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| Design Arena: websites | 1262 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: UI components | 1263 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: game dev | 1248 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: data viz | 1264 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: 3D | 1248 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: all code categories | 1262 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: SVG | 1206 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: ASCII art | 1160 | Not measured | Only GLM 5 Turbo measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GLM 5 Turbo | GPT-5.1-Codex-Max | Leader |
|---|---|---|---|
| IFBench | 73.2% | Not measured | Only GLM 5 Turbo measured |
| Long context reasoning (AA-LCR) | 71.7% | Not measured | Only GLM 5 Turbo measured |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5 Turbo | GPT-5.1-Codex-Max | 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 5 Turbo costs less
Repository review
50K input + 3K output tokens
GLM 5 Turbo costs less
Agent loop
200K input + 10K output tokens
GLM 5 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 5 Turbo | OpenAI GPT-5.1-Codex-Max |
|---|---|---|
| Maker | Z.ai | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | March 15, 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 | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5 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 5 Turbo for output tokens 2.5x cheaper ($4.00 vs $10.00 per million) and work measured by ALE-Bench, where it leads.
Which is cheaper, GLM 5 Turbo or GPT-5.1-Codex-Max?
GLM 5 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 5 Turbo or GPT-5.1-Codex-Max?
GPT-5.1-Codex-Max, with 400K tokens against 203K.
How many benchmarks is the GLM 5 Turbo vs GPT-5.1-Codex-Max comparison based on?
1 benchmarks have a result for both models as of October 21, 2026. GLM 5 Turbo's coding index rests on 0 independent benchmarks and GPT-5.1-Codex-Max's on 1. Where only one model has a result, the page says so instead of naming a winner.