GLM 5 Turbo vs Granite 4.0 Micro
GLM 5 Turbo leads Granite 4.0 Micro on the Artificial Analysis Intelligence Index, 26.6 to 5.1, and Granite 4.0 Micro costs 35.7x less per output token ($0.112 vs $4.00 per million). Updated October 23, 2026; 7 benchmarks have a result for both.
GLM 5 Turbo or Granite 4.0 Micro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 5 Turbo for a larger context window (203K against 131K tokens).
- Shared results
- 7
- GLM 5 Turbo only
- 9
- Granite 4.0 Micro only
- 6
- Like-for-like categories
- 5 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
GLM 5 Turbo
GLM 5 Turbo leads, 26.6 against 5.1.
Same board, both measured
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
GLM 5 Turbo
GLM 5 Turbo takes 203K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Granite 4.0 Micro
GLM 5 Turbo $0.0032, Granite 4.0 Micro $0.0001 per turn.
List prices
At a glance
- Coding index
- GLM 5 Turbo not benchmarked, Granite 4.0 Micro not benchmarked.
- Widest category
- Agentic work, 86.0 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GLM 5 Turbo 98.5% against Granite 4.0 Micro 12.6%, 86.0 points apart on a 0 to 100 scale.
- Output price
- GLM 5 Turbo $4.00 against Granite 4.0 Micro $0.112 per million output tokens, 35.7x apart.
- Context window
- GLM 5 Turbo takes 203K tokens, Granite 4.0 Micro 131K.
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 | Granite 4.0 Micro | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 7 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | GLM 5 Turbo | Granite 4.0 Micro | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 18.0% | Only Granite 4.0 Micro measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | 1.5% | GLM 5 Turbo |
| ALE-Bench | 634.0 | Not measured | Only GLM 5 Turbo measured |
| Neither model has a result on the other 40 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5 Turbo | Granite 4.0 Micro | Leader |
|---|---|---|---|
| AA Intelligence Index | 26.6 | 5.1 | GLM 5 Turbo |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5 Turbo | Granite 4.0 Micro | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 98.5% | 12.6% | GLM 5 Turbo |
| Neither model has a result on the other 41 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5 Turbo | Granite 4.0 Micro | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.7% | 33.6% | GLM 5 Turbo |
| Humanity's Last Exam (Artificial Analysis run) | 27.8% | 5.0% | GLM 5 Turbo |
| GPQA Diamond (Epoch AI run) | Not measured | 28.3% | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GLM 5 Turbo | Granite 4.0 Micro | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 6.0 | Only Granite 4.0 Micro measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 6.0% | Only Granite 4.0 Micro measured |
| OTIS Mock AIME | Not measured | 2.8% | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GLM 5 Turbo | Granite 4.0 Micro | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 44.7% | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 19 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GLM 5 Turbo | Granite 4.0 Micro | Leader |
|---|---|---|---|
| Design Arena: websites | 1262 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: UI components | 1261 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: game dev | 1247 | 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 | 1261 | Not measured | Only GLM 5 Turbo measured |
| Design Arena: SVG | 1205 | 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 | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5 Turbo | Granite 4.0 Micro | Leader |
|---|---|---|---|
| IFBench | 73.2% | 24.8% | GLM 5 Turbo |
| Long context reasoning (AA-LCR) | 71.7% | 7.0% | GLM 5 Turbo |
| Neither model has a result on the other 46 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5 Turbo | Granite 4.0 Micro | 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
Granite 4.0 Micro costs less
Repository review
50K input + 3K output tokens
Granite 4.0 Micro costs less
Agent loop
200K input + 10K output tokens
Granite 4.0 Micro 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 | IBM Granite 4.0 Micro |
|---|---|---|
| Maker | Z.ai | IBM Granite |
| Weights | No public weights listed | Open weights |
| Released | March 15, 2026 | October 20, 2025 |
| Context window | 203K | 131K |
| Input $/Mtok | $1.20 | $0.017 |
| Output $/Mtok | $4.00 | $0.112 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5 Turbo better than Granite 4.0 Micro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5 Turbo for a larger context window (203K against 131K tokens).
Which is cheaper, GLM 5 Turbo or Granite 4.0 Micro?
GLM 5 Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Granite 4.0 Micro costs $0.017 and $0.112. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5 Turbo or Granite 4.0 Micro?
GLM 5 Turbo, with 203K tokens against 131K.
How many benchmarks is the GLM 5 Turbo vs Granite 4.0 Micro comparison based on?
7 benchmarks have a result for both models as of October 23, 2026. GLM 5 Turbo's coding index rests on 0 independent benchmarks and Granite 4.0 Micro's on 0. Where only one model has a result, the page says so instead of naming a winner.