GLM 4.7 Flash vs Granite 4.2 8B
GLM 4.7 Flash leads Granite 4.2 8B on the Artificial Analysis Intelligence Index, 14.9 to 11.1, and Granite 4.2 8B costs 2.0x less per output token ($0.20 vs $0.40 per million). Updated October 22, 2026; 24 benchmarks have a result for both.
GLM 4.7 Flash or Granite 4.2 8B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 4.7 Flash for a larger context window (200K against 131K tokens) and work measured by GPQA Diamond (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.
- Shared results
- 24
- GLM 4.7 Flash only
- 19
- Granite 4.2 8B only
- 3
- 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 4.7 Flash
GLM 4.7 Flash leads, 14.9 against 11.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Granite 4.2 8B has a AA Agentic Index result, 1.3.
Directional only
Web design
Design Arena: websites
No call
Only GLM 4.7 Flash has a Design Arena: websites result, 1194.
Directional only
Long documents
Listed context window
GLM 4.7 Flash
GLM 4.7 Flash takes 200K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Granite 4.2 8B
GLM 4.7 Flash $0.0003, Granite 4.2 8B $0.0002 per turn.
List prices
At a glance
- Coding index
- GLM 4.7 Flash not benchmarked, Granite 4.2 8B not benchmarked.
- Widest category
- General, 6.0 points apart on average over 12 shared benchmarks.
- Widest single gap
- LMArena Text: creative writing: GLM 4.7 Flash 1296 against Granite 4.2 8B 1236, 10.0 points apart on a 0 to 100 scale.
- Output price
- GLM 4.7 Flash $0.40 against Granite 4.2 8B $0.20 per million output tokens, 2.0x apart.
- Context window
- GLM 4.7 Flash takes 200K tokens, Granite 4.2 8B 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 4.7 Flash | Bars | Granite 4.2 8B | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 3 | ||
| Knowledge | 4 | 0 | ||
| General | 11 | 1 | ||
| All shared boards | 20 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | GLM 4.7 Flash | Granite 4.2 8B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 22.4 | Only Granite 4.2 8B measured |
| SciCode | Not measured | 31.5% | Only Granite 4.2 8B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 22.0% | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: coding | 1382 | 1378 | GLM 4.7 Flash |
| LMArena Text: software and IT | 1389 | 1367 | GLM 4.7 Flash |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 4.7 Flash | Granite 4.2 8B | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.9 | 11.1 | GLM 4.7 Flash |
| 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 4.7 Flash | Granite 4.2 8B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.3 | Only Granite 4.2 8B measured |
| τ²-Bench Telecom | 98.8% | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | GLM 4.7 Flash | Granite 4.2 8B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 58.1% | 63.1% | Granite 4.2 8B |
| Humanity's Last Exam (Artificial Analysis run) | 7.6% | 9.7% | Granite 4.2 8B |
| GPQA Diamond (Epoch AI run) | 60.5% | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: hard prompts | 1356 | 1327 | GLM 4.7 Flash |
| LMArena Text: expert | 1357 | 1386 | Granite 4.2 8B |
| LMArena Text: hard prompts in English | 1369 | 1345 | GLM 4.7 Flash |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GLM 4.7 Flash | Granite 4.2 8B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 58.3% | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: math | 1355 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: mathematical work | 1369 | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GLM 4.7 Flash | Granite 4.2 8B | Leader |
|---|---|---|---|
| LMArena Text: science | 1358 | 1336 | GLM 4.7 Flash |
| LMArena Text: medicine and healthcare | 1343 | 1336 | GLM 4.7 Flash |
| LMArena Text: legal and government | 1357 | 1327 | GLM 4.7 Flash |
| LMArena Text: business and finance | 1343 | 1322 | GLM 4.7 Flash |
| Neither model has a result on the other 14 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GLM 4.7 Flash | Granite 4.2 8B | Leader |
|---|---|---|---|
| Design Arena: websites | 1194 | Not measured | Only GLM 4.7 Flash measured |
| Design Arena: UI components | 1205 | Not measured | Only GLM 4.7 Flash measured |
| Design Arena: game dev | 1134 | Not measured | Only GLM 4.7 Flash measured |
| Design Arena: data viz | 1123 | Not measured | Only GLM 4.7 Flash measured |
| Design Arena: 3D | 1120 | Not measured | Only GLM 4.7 Flash measured |
| Design Arena: all code categories | 1177 | Not measured | Only GLM 4.7 Flash measured |
| Design Arena: SVG | 1037 | Not measured | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index111
| Benchmark | GLM 4.7 Flash | Granite 4.2 8B | Leader |
|---|---|---|---|
| IFBench | 60.8% | Not measured | Only GLM 4.7 Flash measured |
| Long context reasoning (AA-LCR) | 41.7% | 45.0% | Granite 4.2 8B |
| LMArena Text | 1351 | 1319 | GLM 4.7 Flash |
| LMArena Text: instruction following | 1327 | 1300 | GLM 4.7 Flash |
| LMArena Text: creative writing | 1296 | 1236 | GLM 4.7 Flash |
| LMArena Text: English | 1373 | 1337 | GLM 4.7 Flash |
| LMArena Text: non-English | 1330 | 1301 | GLM 4.7 Flash |
| LMArena Text: Chinese | 1403 | 1367 | GLM 4.7 Flash |
| LMArena Text: German | 1336 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Korean | 1283 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: French | 1332 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Spanish | 1350 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: Russian | 1333 | 1282 | GLM 4.7 Flash |
| LMArena Text: Polish | 1291 | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: multi-turn | 1342 | 1301 | GLM 4.7 Flash |
| LMArena Text: longer queries | 1345 | 1325 | GLM 4.7 Flash |
| LMArena Text: writing and language | 1320 | 1269 | GLM 4.7 Flash |
| LMArena Text: entertainment and media | 1304 | 1271 | GLM 4.7 Flash |
| Neither model has a result on the other 28 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.7 Flash | Granite 4.2 8B | 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 4.2 8B costs less
Repository review
50K input + 3K output tokens
GLM 4.7 Flash costs less
Agent loop
200K input + 10K output tokens
GLM 4.7 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 | Z.ai GLM 4.7 Flash | IBM Granite 4.2 8B |
|---|---|---|
| Maker | Z.ai | IBM Granite |
| Weights | Open weights | Open weights |
| Released | January 19, 2026 | August 31, 2026 |
| Context window | 200K | 131K |
| Input $/Mtok | $0.0653 | $0.08 |
| Output $/Mtok | $0.40 | $0.20 |
| 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 4.7 Flash better than Granite 4.2 8B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for a larger context window (200K against 131K tokens) and work measured by GPQA Diamond (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.
Which is cheaper, GLM 4.7 Flash or Granite 4.2 8B?
GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; Granite 4.2 8B costs $0.08 and $0.20. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 4.7 Flash or Granite 4.2 8B?
GLM 4.7 Flash, with 200K tokens against 131K.
How many benchmarks is the GLM 4.7 Flash vs Granite 4.2 8B comparison based on?
24 benchmarks have a result for both models as of October 22, 2026. GLM 4.7 Flash's coding index rests on 0 independent benchmarks and Granite 4.2 8B's on 0. Where only one model has a result, the page says so instead of naming a winner.