Model comparison
GLM-4.7-Flash vs Mercury
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 37.6 on the Noometry Index.
Last verified . 8 shared benchmarks.
Summary
- They share 8 benchmarks with published results for both. GLM-4.7-Flash scores higher in 6 categories and Mercury in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.7-Flash leads 46.5 to 41.6.
- GLM-4.7-Flash has downloadable open weights; the other is API-only.
Side by side
| GLM-4.7-Flash | Mercury | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Inception |
| Noometry Index | 38.8 | 37.6 |
| Released | 2026-01-19 | — |
| Weights | Open | Proprietary |
| Context window | 200K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.06 | — |
| Output $ / M tokens | $0.40 | — |
| Results tracked | 21 | 9 |
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Category by category
Coding GLM-4.7-Flash leads
GLM-4.7-Flash: 40.6 (#135), Mercury: 38.7 (#170)
| Benchmark | GLM-4.7-Flash | Mercury |
|---|---|---|
| LMArena Coding | 1383 | 1322 |
Reasoning GLM-4.7-Flash leads
GLM-4.7-Flash: 20.9 (#229), Mercury: 17.5 (#293)
| Benchmark | GLM-4.7-Flash | Mercury |
|---|---|---|
| LMArena Hard Prompts | 1356 | 1285 |
| Kagi LLM Benchmark | — | 21.6% |
| Chess Puzzles | 0% | — |
Math Not comparable
GLM-4.7-Flash: 36.1 (#173), Mercury: —
| Benchmark | GLM-4.7-Flash | Mercury |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | — |
| LMArena Math | 1355 | — |
Knowledge Not comparable
GLM-4.7-Flash: 35.5 (#184), Mercury: —
| Benchmark | GLM-4.7-Flash | Mercury |
|---|---|---|
| GPQA Diamond | 60.5% | — |
| Vectara Hallucination Rate | 9.3% | — |
| LMArena Expert | 1357 | — |
Multilingual GLM-4.7-Flash leads
GLM-4.7-Flash: 46.5 (#158), Mercury: 41.6 (#206)
| Benchmark | GLM-4.7-Flash | Mercury |
|---|---|---|
| LMArena Non-English | 1330 | 1260 |
| LMArena Chinese | 1403 | — |
| LMArena French | 1332 | — |
| LMArena German | 1337 | — |
| LMArena Korean | 1283 | — |
| LMArena Russian | 1332 | — |
| LMArena Spanish | 1350 | — |
Instruction Following GLM-4.7-Flash leads
GLM-4.7-Flash: 70.1 (#167), Mercury: 65.2 (#224)
| Benchmark | GLM-4.7-Flash | Mercury |
|---|---|---|
| LMArena Instruction Following | 1327 | 1239 |
Long Context GLM-4.7-Flash leads
GLM-4.7-Flash: 40.9 (#148), Mercury: 38.4 (#198)
| Benchmark | GLM-4.7-Flash | Mercury |
|---|---|---|
| LMArena Longer Query | 1345 | 1266 |
Writing & Preference GLM-4.7-Flash leads
GLM-4.7-Flash: 47.4 (#210), Mercury: 46.2 (#221)
| Benchmark | GLM-4.7-Flash | Mercury |
|---|---|---|
| LMArena Text | 1351 | 1282 |
| LMArena Creative Writing | 1297 | 1191 |
| LMArena Multi-Turn | 1342 | 1282 |
| EQ-Bench Creative Writing | 1125 | — |
Frequently asked questions
Is GLM-4.7-Flash better than Mercury?
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 37.6 on the Noometry Index.
Is GLM-4.7-Flash or Mercury better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 38.7 in the Noometry coding category.
How many benchmarks do GLM-4.7-Flash and Mercury share?
8 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Mercury has 9.