Model comparison
GLM-5.3-Flash vs Grok 4.1 Fast
GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 40.9 on the Noometry Index.
Last verified . 21 shared benchmarks.
Summary
- They share 21 benchmarks with published results for both. GLM-5.3-Flash scores higher in 8 categories and Grok 4.1 Fast in 2 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 32.6.
- The biggest single-benchmark swing is ProofBench: 21% for GLM-5.3-Flash and 4% for Grok 4.1 Fast.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $0.20 / $0.50 for Grok 4.1 Fast.
- GLM-5.3-Flash accepts more context: 1M tokens versus 128K.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| GLM-5.3-Flash | Grok 4.1 Fast | |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 49.6 | 40.9 |
| Released | 2026-08-20 | 2025-06-27 |
| Weights | Open | Proprietary |
| Context window | 1M | 128K |
| Max output | 131K | 30K |
| Input $ / M tokens | $0.15 | $0.20 |
| Output $ / M tokens | $0.50 | $0.50 |
| Results tracked | 36 | 32 |
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Category by category
Coding GLM-5.3-Flash leads
GLM-5.3-Flash: 53.7 (#26), Grok 4.1 Fast: 33.8 (#236)
| Benchmark | GLM-5.3-Flash | Grok 4.1 Fast |
|---|---|---|
| LMArena WebDev | 1614 | 1241 |
| LMArena Coding | 1506 | 1411 |
| ALE-Bench | 303.55 | 394.93 |
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| SciCode | 51.6% | — |
Agentic & Tool Use Grok 4.1 Fast leads
GLM-5.3-Flash: 34.3 (#41), Grok 4.1 Fast: 36.1 (#35)
| Benchmark | GLM-5.3-Flash | Grok 4.1 Fast |
|---|---|---|
| APEX-Agents | 52.8% | — |
| Berkeley Function Calling Leaderboard | — | 69.6% |
| τ²-bench Banking | — | 13.1% |
| GDP.pdf | 14% | — |
| LMArena Search | — | 1171 |
| Vending-Bench 2 | — | 1,107 |
Reasoning Grok 4.1 Fast leads
GLM-5.3-Flash: 31.7 (#69), Grok 4.1 Fast: 42.3 (#45)
| Benchmark | GLM-5.3-Flash | Grok 4.1 Fast |
|---|---|---|
| LMArena Hard Prompts | 1490 | 1407 |
| SimpleBench | — | 56% |
| NYT Connections (extended) | — | 87.4% |
| CritPt | 15.4% | — |
| Chess Puzzles | 14% | — |
| Mystery Game Puzzles | 8% | — |
| DTBench | — | 87.7% |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
| Epoch Capabilities Index | 151.9 | — |
| ForecastBench | — | 61 |
Math GLM-5.3-Flash leads
GLM-5.3-Flash: 53.1 (#38), Grok 4.1 Fast: 30.9 (#201)
| Benchmark | GLM-5.3-Flash | Grok 4.1 Fast |
|---|---|---|
| ProofBench | 21% | 4% |
| LMArena Math | 1499 | 1408 |
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
| MathArena Final-Answer Competitions | — | 60.9% |
| OTIS Mock AIME 2024-2025 | 93.9% | — |
Knowledge GLM-5.3-Flash leads
GLM-5.3-Flash: 58.4 (#33), Grok 4.1 Fast: 32.6 (#203)
| Benchmark | GLM-5.3-Flash | Grok 4.1 Fast |
|---|---|---|
| LMArena Expert | 1512 | 1398 |
| GPQA Diamond | 90.2% | — |
| Vectara Hallucination Rate | — | 17.8% |
Multimodal GLM-5.3-Flash leads
GLM-5.3-Flash: 42.6 (#25), Grok 4.1 Fast: 36.3 (#71)
| Benchmark | GLM-5.3-Flash | Grok 4.1 Fast |
|---|---|---|
| LMArena Vision | 1304 | 1201 |
Multilingual GLM-5.3-Flash leads
GLM-5.3-Flash: 56.2 (#24), Grok 4.1 Fast: 51.1 (#110)
| Benchmark | GLM-5.3-Flash | Grok 4.1 Fast |
|---|---|---|
| LMArena Non-English | 1462 | 1391 |
| LMArena Chinese | 1529 | 1441 |
| LMArena French | 1495 | 1416 |
| LMArena German | 1457 | 1404 |
| LMArena Japanese | 1420 | 1347 |
| LMArena Korean | 1443 | 1361 |
| LMArena Russian | 1472 | 1387 |
| LMArena Spanish | 1471 | 1411 |
Instruction Following GLM-5.3-Flash leads
GLM-5.3-Flash: 77.8 (#17), Grok 4.1 Fast: 72.8 (#127)
| Benchmark | GLM-5.3-Flash | Grok 4.1 Fast |
|---|---|---|
| LMArena Instruction Following | 1480 | 1376 |
Long Context GLM-5.3-Flash leads
GLM-5.3-Flash: 45.3 (#41), Grok 4.1 Fast: 42.4 (#121)
| Benchmark | GLM-5.3-Flash | Grok 4.1 Fast |
|---|---|---|
| LMArena Longer Query | 1479 | 1390 |
Writing & Preference GLM-5.3-Flash leads
GLM-5.3-Flash: 65.4 (#49), Grok 4.1 Fast: 57.4 (#126)
| Benchmark | GLM-5.3-Flash | Grok 4.1 Fast |
|---|---|---|
| LMArena Text | 1471 | 1408 |
| LMArena Creative Writing | 1440 | 1394 |
| LMArena Multi-Turn | 1471 | 1389 |
| EQ-Bench Creative Writing | — | 1327 |
Frequently asked questions
Is GLM-5.3-Flash better than Grok 4.1 Fast?
GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 40.9 on the Noometry Index.
Which is cheaper, GLM-5.3-Flash or Grok 4.1 Fast?
GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Grok 4.1 Fast lists at $0.20 and $0.50.
Is GLM-5.3-Flash or Grok 4.1 Fast better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 33.8 in the Noometry coding category.
Which has the bigger context window?
GLM-5.3-Flash does, with 1M tokens against 128K.
How many benchmarks do GLM-5.3-Flash and Grok 4.1 Fast share?
21 benchmarks have published results for both models. GLM-5.3-Flash has 36 scored results on Noometry and Grok 4.1 Fast has 32.