Model comparison
GLM-4.7-Flash vs Sonar
GLM-4.7-Flash and Sonar score almost the same on the Noometry Index (38.8 vs 38.5), so choose on price, context window or the category you care about most.
Last verified . 0 shared benchmarks.
PerplexitySummary
- The widest gap is in writing & preference, where Sonar leads 52.6 to 47.4.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $1 / $1 for Sonar.
- GLM-4.7-Flash accepts more context: 200K tokens versus 128K.
- GLM-4.7-Flash has downloadable open weights; the other is API-only.
Side by side
| GLM-4.7-Flash | Sonar | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Perplexity |
| Noometry Index | 38.8 | 38.5 |
| Released | 2026-01-19 | 2024-01-01 |
| Weights | Open | Proprietary |
| Context window | 200K | 128K |
| Max output | 131K | 4K |
| Input $ / M tokens | $0.06 | $1 |
| Output $ / M tokens | $0.40 | $1 |
| Results tracked | 21 | 7 |
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Category by category
Coding GLM-4.7-Flash leads
GLM-4.7-Flash: 40.6 (#135), Sonar: 35.7 (#221)
| Benchmark | GLM-4.7-Flash | Sonar |
|---|---|---|
| LiveBench Coding | — | 35.1% |
| LMArena Coding | 1383 | — |
Reasoning Too close to call
GLM-4.7-Flash: 20.9 (#229), Sonar: 21.1 (#227)
| Benchmark | GLM-4.7-Flash | Sonar |
|---|---|---|
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | — | 46.3% |
| LMArena Hard Prompts | 1356 | — |
| LiveBench Data Analysis | — | 37.9% |
| LiveBench | — | 46.9% |
Math GLM-4.7-Flash leads
GLM-4.7-Flash: 36.1 (#173), Sonar: 33.7 (#200)
| Benchmark | GLM-4.7-Flash | Sonar |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | — |
| LiveBench Math | — | 41.6% |
| LMArena Math | 1355 | — |
Knowledge Not comparable
GLM-4.7-Flash: 35.5 (#184), Sonar: —
| Benchmark | GLM-4.7-Flash | Sonar |
|---|---|---|
| GPQA Diamond | 60.5% | — |
| Vectara Hallucination Rate | 9.3% | — |
| LMArena Expert | 1357 | — |
Multilingual Not comparable
GLM-4.7-Flash: 46.5 (#158), Sonar: —
| Benchmark | GLM-4.7-Flash | Sonar |
|---|---|---|
| LMArena Non-English | 1330 | — |
| LMArena Chinese | 1403 | — |
| LMArena French | 1332 | — |
| LMArena German | 1337 | — |
| LMArena Korean | 1283 | — |
| LMArena Russian | 1332 | — |
| LMArena Spanish | 1350 | — |
Instruction Following Sonar leads
GLM-4.7-Flash: 70.1 (#167), Sonar: 71.4 (#150)
| Benchmark | GLM-4.7-Flash | Sonar |
|---|---|---|
| LiveBench Instruction Following | — | 76.2% |
| LMArena Instruction Following | 1327 | — |
Long Context Not comparable
GLM-4.7-Flash: 40.9 (#148), Sonar: —
| Benchmark | GLM-4.7-Flash | Sonar |
|---|---|---|
| LMArena Longer Query | 1345 | — |
Writing & Preference Sonar leads
GLM-4.7-Flash: 47.4 (#210), Sonar: 52.6 (#167)
| Benchmark | GLM-4.7-Flash | Sonar |
|---|---|---|
| LMArena Text | 1351 | — |
| LMArena Creative Writing | 1297 | — |
| EQ-Bench Creative Writing | 1125 | — |
| LMArena Multi-Turn | 1342 | — |
| LiveBench Language | — | 44.1% |
Frequently asked questions
Is GLM-4.7-Flash better than Sonar?
GLM-4.7-Flash and Sonar score almost the same on the Noometry Index (38.8 vs 38.5), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-4.7-Flash or Sonar?
GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Sonar lists at $1 and $1.
Is GLM-4.7-Flash or Sonar better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 35.7 in the Noometry coding category.
Which has the bigger context window?
GLM-4.7-Flash does, with 200K tokens against 128K.
How many benchmarks do GLM-4.7-Flash and Sonar share?
0 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Sonar has 7.