Model comparison
GLM-5.3-Flash vs Granite 4.2 8B
GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 40.0 on the Noometry Index. Granite 4.2 8B costs 2.2× less per token, which makes it the better buy when GLM-5.3-Flash's lead doesn't matter for your workload.
Last verified . 11 shared benchmarks.
Summary
- They share 11 benchmarks with published results for both. GLM-5.3-Flash scores higher in 7 categories and Granite 4.2 8B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 37.7.
- Granite 4.2 8B is cheaper at $0.06 / $0.25 per million input/output tokens, against $0.15 / $0.50 for GLM-5.3-Flash.
- GLM-5.3-Flash accepts more context: 1M tokens versus 131K.
Side by side
| GLM-5.3-Flash | Granite 4.2 8B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | IBM |
| Noometry Index | 49.6 | 40.0 |
| Released | 2026-08-20 | — |
| Weights | Open | Open |
| Context window | 1M | 131K |
| Max output | 131K | 118K |
| Input $ / M tokens | $0.15 | $0.06 |
| Output $ / M tokens | $0.50 | $0.25 |
| Results tracked | 36 | 11 |
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Category by category
Coding GLM-5.3-Flash leads
GLM-5.3-Flash: 53.7 (#26), Granite 4.2 8B: 39.9 (#138)
| Benchmark | GLM-5.3-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Coding | 1506 | 1379 |
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| LMArena WebDev | 1614 | — |
| SciCode | 51.6% | — |
| ALE-Bench | 303.55 | — |
Agentic & Tool Use Not comparable
GLM-5.3-Flash: 34.3 (#41), Granite 4.2 8B: —
| Benchmark | GLM-5.3-Flash | Granite 4.2 8B |
|---|---|---|
| APEX-Agents | 52.8% | — |
| GDP.pdf | 14% | — |
Reasoning GLM-5.3-Flash leads
GLM-5.3-Flash: 31.7 (#69), Granite 4.2 8B: 25.5 (#130)
| Benchmark | GLM-5.3-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Hard Prompts | 1490 | 1327 |
| CritPt | 15.4% | — |
| Chess Puzzles | 14% | — |
| Mystery Game Puzzles | 8% | — |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
| Epoch Capabilities Index | 151.9 | — |
Math Not comparable
GLM-5.3-Flash: 53.1 (#38), Granite 4.2 8B: —
| Benchmark | GLM-5.3-Flash | Granite 4.2 8B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
| OTIS Mock AIME 2024-2025 | 93.9% | — |
| ProofBench | 21% | — |
| LMArena Math | 1499 | — |
Knowledge GLM-5.3-Flash leads
GLM-5.3-Flash: 58.4 (#33), Granite 4.2 8B: 37.7 (#144)
| Benchmark | GLM-5.3-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Expert | 1512 | 1380 |
| GPQA Diamond | 90.2% | — |
Multimodal Not comparable
GLM-5.3-Flash: 42.6 (#25), Granite 4.2 8B: —
| Benchmark | GLM-5.3-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Vision | 1304 | — |
Multilingual GLM-5.3-Flash leads
GLM-5.3-Flash: 56.2 (#24), Granite 4.2 8B: 44.5 (#173)
| Benchmark | GLM-5.3-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Non-English | 1462 | 1299 |
| LMArena Chinese | 1529 | 1361 |
| LMArena Russian | 1472 | 1283 |
| LMArena French | 1495 | — |
| LMArena German | 1457 | — |
| LMArena Japanese | 1420 | — |
| LMArena Korean | 1443 | — |
| LMArena Spanish | 1471 | — |
Instruction Following GLM-5.3-Flash leads
GLM-5.3-Flash: 77.8 (#17), Granite 4.2 8B: 68.7 (#183)
| Benchmark | GLM-5.3-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Instruction Following | 1480 | 1298 |
Long Context GLM-5.3-Flash leads
GLM-5.3-Flash: 45.3 (#41), Granite 4.2 8B: 40.2 (#154)
| Benchmark | GLM-5.3-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Longer Query | 1479 | 1323 |
Writing & Preference GLM-5.3-Flash leads
GLM-5.3-Flash: 65.4 (#49), Granite 4.2 8B: 49.8 (#183)
| Benchmark | GLM-5.3-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Text | 1471 | 1319 |
| LMArena Creative Writing | 1440 | 1238 |
| LMArena Multi-Turn | 1471 | 1299 |
Frequently asked questions
Is GLM-5.3-Flash better than Granite 4.2 8B?
GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 40.0 on the Noometry Index. Granite 4.2 8B costs 2.2× less per token, which makes it the better buy when GLM-5.3-Flash's lead doesn't matter for your workload.
Which is cheaper, GLM-5.3-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-5.3-Flash lists at $0.15 and $0.50.
Is GLM-5.3-Flash or Granite 4.2 8B better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 39.9 in the Noometry coding category.
Which has the bigger context window?
GLM-5.3-Flash does, with 1M tokens against 131K.
How many benchmarks do GLM-5.3-Flash and Granite 4.2 8B share?
11 benchmarks have published results for both models. GLM-5.3-Flash has 36 scored results on Noometry and Granite 4.2 8B has 11.