Model comparison
GLM-4.7-Flash vs Granite 4.2 8B
Granite 4.2 8B is the stronger model overall, scoring 40.5 to 38.8 on the Noometry Index.
Last verified . 11 shared benchmarks.
Summary
- They share 11 benchmarks with published results for both. GLM-4.7-Flash scores higher in 4 categories and Granite 4.2 8B in 3 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Granite 4.2 8B leads 26.6 to 20.9.
- Granite 4.2 8B is cheaper at $0.06 / $0.25 per million input/output tokens, against $0.06 / $0.40 for GLM-4.7-Flash.
- GLM-4.7-Flash accepts more context: 200K tokens versus 131K.
Side by side
| GLM-4.7-Flash | Granite 4.2 8B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | IBM |
| Noometry Index | 38.8 | 40.5 |
| Released | 2026-01-19 | — |
| Weights | Open | Open |
| Context window | 200K | 131K |
| Max output | 131K | 118K |
| Input $ / M tokens | $0.06 | $0.06 |
| Output $ / M tokens | $0.40 | $0.25 |
| Results tracked | 21 | 11 |
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Category by category
Coding Too close to call
GLM-4.7-Flash: 40.6 (#135), Granite 4.2 8B: 40.5 (#137)
| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Coding | 1383 | 1380 |
Reasoning Granite 4.2 8B leads
GLM-4.7-Flash: 20.9 (#229), Granite 4.2 8B: 26.6 (#131)
| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Hard Prompts | 1356 | 1329 |
| Chess Puzzles | 0% | — |
Math Not comparable
GLM-4.7-Flash: 36.1 (#173), Granite 4.2 8B: —
| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | — |
| LMArena Math | 1355 | — |
Knowledge Granite 4.2 8B leads
GLM-4.7-Flash: 35.5 (#184), Granite 4.2 8B: 38.4 (#145)
| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Expert | 1357 | 1384 |
| GPQA Diamond | 60.5% | — |
| Vectara Hallucination Rate | 9.3% | — |
Multilingual GLM-4.7-Flash leads
GLM-4.7-Flash: 46.5 (#158), Granite 4.2 8B: 44.5 (#178)
| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Non-English | 1330 | 1302 |
| LMArena Chinese | 1403 | 1366 |
| LMArena Russian | 1332 | 1285 |
| LMArena French | 1332 | — |
| LMArena German | 1337 | — |
| LMArena Korean | 1283 | — |
| LMArena Spanish | 1350 | — |
Instruction Following GLM-4.7-Flash leads
GLM-4.7-Flash: 70.1 (#167), Granite 4.2 8B: 68.7 (#184)
| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Instruction Following | 1327 | 1301 |
Long Context Too close to call
GLM-4.7-Flash: 40.9 (#148), Granite 4.2 8B: 40.3 (#159)
| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Longer Query | 1345 | 1324 |
Writing & Preference Granite 4.2 8B leads
GLM-4.7-Flash: 47.4 (#210), Granite 4.2 8B: 49.6 (#189)
| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Text | 1351 | 1320 |
| LMArena Creative Writing | 1297 | 1236 |
| LMArena Multi-Turn | 1342 | 1301 |
| EQ-Bench Creative Writing | 1125 | — |
Frequently asked questions
Is GLM-4.7-Flash better than Granite 4.2 8B?
Granite 4.2 8B is the stronger model overall, scoring 40.5 to 38.8 on the Noometry Index.
Which is cheaper, GLM-4.7-Flash or Granite 4.2 8B?
Granite 4.2 8B is cheaper. It lists at $0.06 per million input tokens and $0.25 per million output tokens; GLM-4.7-Flash lists at $0.06 and $0.40.
Is GLM-4.7-Flash or Granite 4.2 8B better for coding?
They score almost the same on coding (40.6 vs 40.5); test both on your own repository before choosing.
Which has the bigger context window?
GLM-4.7-Flash does, with 200K tokens against 131K.
How many benchmarks do GLM-4.7-Flash and Granite 4.2 8B share?
11 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Granite 4.2 8B has 11.