Model comparison
GLM-4.7-Flash vs MiniMax-M3
MiniMax-M3 is the stronger model overall, scoring 43.8 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 3.6× less per token, which makes it the better buy when MiniMax-M3's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
MiniMaxSummary
- They share 19 benchmarks with published results for both. GLM-4.7-Flash scores higher in 0 categories and MiniMax-M3 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where MiniMax-M3 leads 58.4 to 35.5.
- The biggest single-benchmark swing is GPQA Diamond: 60.5% for GLM-4.7-Flash and 90.9% for MiniMax-M3.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M3.
- MiniMax-M3 accepts more context: 1M tokens versus 200K.
Side by side
| GLM-4.7-Flash | MiniMax-M3 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | MiniMax |
| Noometry Index | 38.8 | 43.8 |
| Released | 2026-01-19 | 2026-06-01 |
| Weights | Open | Open |
| Context window | 200K | 1M |
| Max output | 131K | 512K |
| Input $ / M tokens | $0.06 | $0.30 |
| Output $ / M tokens | $0.40 | $1.20 |
| Results tracked | 21 | 41 |
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Category by category
Coding MiniMax-M3 leads
GLM-4.7-Flash: 40.6 (#135), MiniMax-M3: 41.8 (#118)
| Benchmark | GLM-4.7-Flash | MiniMax-M3 |
|---|---|---|
| LMArena Coding | 1383 | 1469 |
| FrontierCode | — | 14.7% |
| LMArena WebDev | — | 1482 |
| SciCode | — | 47.1% |
| ALE-Bench | — | 640.02 |
Agentic & Tool Use Not comparable
GLM-4.7-Flash: —, MiniMax-M3: 22.6 (#130)
| Benchmark | GLM-4.7-Flash | MiniMax-M3 |
|---|---|---|
| APEX-Agents | — | 37.7% |
| OSWorld 2.0 | — | 4.6% |
| GBAEval | — | 0.9% |
| Vending-Bench 2 | — | 2,158 |
Reasoning MiniMax-M3 leads
GLM-4.7-Flash: 20.9 (#229), MiniMax-M3: 30.1 (#87)
| Benchmark | GLM-4.7-Flash | MiniMax-M3 |
|---|---|---|
| Chess Puzzles | 0% | 14% |
| LMArena Hard Prompts | 1356 | 1447 |
| SimpleBench | — | 45.8% |
| NYT Connections (extended) | — | 65.1% |
| CritPt | — | 3.7% |
| Mystery Game Puzzles | — | 8% |
| DTBench | — | 78.9% |
| LMCA | — | 33.7% |
| Surface Evolver Bench | — | 55% |
| Epoch Capabilities Index | — | 146.95 |
| ForecastBench | — | 61.4 |
Math MiniMax-M3 leads
GLM-4.7-Flash: 36.1 (#173), MiniMax-M3: 40.0 (#95)
| Benchmark | GLM-4.7-Flash | MiniMax-M3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | 71.1% |
| LMArena Math | 1355 | 1429 |
| ProofBench | — | 18% |
Knowledge MiniMax-M3 leads
GLM-4.7-Flash: 35.5 (#184), MiniMax-M3: 58.4 (#35)
| Benchmark | GLM-4.7-Flash | MiniMax-M3 |
|---|---|---|
| GPQA Diamond | 60.5% | 90.9% |
| LMArena Expert | 1357 | 1461 |
| Vectara Hallucination Rate | 9.3% | — |
Multimodal Not comparable
GLM-4.7-Flash: —, MiniMax-M3: 40.2 (#51)
| Benchmark | GLM-4.7-Flash | MiniMax-M3 |
|---|---|---|
| LMArena Vision | — | 1253 |
| LMArena Document | — | 1435 |
Multilingual MiniMax-M3 leads
GLM-4.7-Flash: 46.5 (#158), MiniMax-M3: 53.0 (#75)
| Benchmark | GLM-4.7-Flash | MiniMax-M3 |
|---|---|---|
| LMArena Non-English | 1330 | 1420 |
| LMArena Chinese | 1403 | 1463 |
| LMArena French | 1332 | 1447 |
| LMArena German | 1337 | 1426 |
| LMArena Korean | 1283 | 1372 |
| LMArena Russian | 1332 | 1428 |
| LMArena Spanish | 1350 | 1432 |
| LMArena Japanese | — | 1381 |
Instruction Following MiniMax-M3 leads
GLM-4.7-Flash: 70.1 (#167), MiniMax-M3: 75.5 (#62)
| Benchmark | GLM-4.7-Flash | MiniMax-M3 |
|---|---|---|
| LMArena Instruction Following | 1327 | 1433 |
Long Context MiniMax-M3 leads
GLM-4.7-Flash: 40.9 (#148), MiniMax-M3: 44.2 (#72)
| Benchmark | GLM-4.7-Flash | MiniMax-M3 |
|---|---|---|
| LMArena Longer Query | 1345 | 1445 |
Writing & Preference MiniMax-M3 leads
GLM-4.7-Flash: 47.4 (#210), MiniMax-M3: 62.1 (#83)
| Benchmark | GLM-4.7-Flash | MiniMax-M3 |
|---|---|---|
| LMArena Text | 1351 | 1433 |
| LMArena Creative Writing | 1297 | 1404 |
| LMArena Multi-Turn | 1342 | 1442 |
| EQ-Bench Creative Writing | 1125 | — |
| EQ-Bench 4 | — | 1150 |
Frequently asked questions
Is GLM-4.7-Flash better than MiniMax-M3?
MiniMax-M3 is the stronger model overall, scoring 43.8 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 3.6× less per token, which makes it the better buy when MiniMax-M3's lead doesn't matter for your workload.
Which is cheaper, GLM-4.7-Flash or MiniMax-M3?
GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; MiniMax-M3 lists at $0.30 and $1.20.
Is GLM-4.7-Flash or MiniMax-M3 better for coding?
MiniMax-M3 scores higher on coding benchmarks: 41.8 versus 40.6 in the Noometry coding category.
Which has the bigger context window?
MiniMax-M3 does, with 1M tokens against 200K.
How many benchmarks do GLM-4.7-Flash and MiniMax-M3 share?
19 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and MiniMax-M3 has 41.