Model comparison
GLM-4.5 vs Sonar
GLM-4.5 is the stronger model overall, scoring 42.0 to 38.5 on the Noometry Index.
Last verified . 0 shared benchmarks.
PerplexitySummary
- The widest gap is in reasoning, where GLM-4.5 leads 28.6 to 21.1.
- Both cost about the same: $0.60 input and $2.20 output per million tokens.
- GLM-4.5 accepts more context: 131K tokens versus 128K.
- GLM-4.5 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5 | Sonar | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Perplexity |
| Noometry Index | 42.0 | 38.5 |
| Released | 2025-07-27 | 2024-01-01 |
| Weights | Open | Proprietary |
| Context window | 131K | 128K |
| Max output | 98K | 4K |
| Input $ / M tokens | $0.60 | $1 |
| Output $ / M tokens | $2.20 | $1 |
| Results tracked | 27 | 7 |
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Category by category
Coding GLM-4.5 leads
GLM-4.5: 41.4 (#125), Sonar: 35.7 (#221)
| Benchmark | GLM-4.5 | Sonar |
|---|---|---|
| SWE-bench Verified (bash only) | 54.2% | — |
| WeirdML | 40.6% | — |
| LiveBench Coding | — | 35.1% |
| LMArena Coding | 1434 | — |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), Sonar: 21.1 (#227)
| Benchmark | GLM-4.5 | Sonar |
|---|---|---|
| Kagi LLM Benchmark | 57.9% | — |
| LiveBench Reasoning | — | 46.3% |
| LMArena Hard Prompts | 1429 | — |
| LiveBench Data Analysis | — | 37.9% |
| LiveBench | — | 46.9% |
Math GLM-4.5 leads
GLM-4.5: 39.0 (#116), Sonar: 33.7 (#200)
| Benchmark | GLM-4.5 | Sonar |
|---|---|---|
| LiveBench Math | — | 41.6% |
| LMArena Math | 1427 | — |
Knowledge Not comparable
GLM-4.5: 35.9 (#179), Sonar: —
| Benchmark | GLM-4.5 | Sonar |
|---|---|---|
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
| LMArena Expert | 1433 | — |
Multilingual Not comparable
GLM-4.5: 52.8 (#77), Sonar: —
| Benchmark | GLM-4.5 | Sonar |
|---|---|---|
| LMArena Non-English | 1417 | — |
| LMArena Chinese | 1465 | — |
| LMArena French | 1418 | — |
| LMArena German | 1407 | — |
| LMArena Japanese | 1415 | — |
| LMArena Korean | 1380 | — |
| LMArena Russian | 1414 | — |
| LMArena Spanish | 1454 | — |
Instruction Following GLM-4.5 leads
GLM-4.5: 74.1 (#104), Sonar: 71.4 (#150)
| Benchmark | GLM-4.5 | Sonar |
|---|---|---|
| LiveBench Instruction Following | — | 76.2% |
| LMArena Instruction Following | 1404 | — |
Long Context Not comparable
GLM-4.5: 38.2 (#201), Sonar: —
| Benchmark | GLM-4.5 | Sonar |
|---|---|---|
| Fiction.LiveBench | 58.3% | — |
| LMArena Longer Query | 1412 | — |
Writing & Preference GLM-4.5 leads
GLM-4.5: 57.5 (#127), Sonar: 52.6 (#167)
| Benchmark | GLM-4.5 | Sonar |
|---|---|---|
| LMArena Text | 1430 | — |
| LMArena Creative Writing | 1395 | — |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
| LMArena Multi-Turn | 1415 | — |
| LiveBench Language | — | 44.1% |
Frequently asked questions
Is GLM-4.5 better than Sonar?
GLM-4.5 is the stronger model overall, scoring 42.0 to 38.5 on the Noometry Index.
Which is cheaper, GLM-4.5 or Sonar?
Sonar is cheaper. It lists at $1 per million input tokens and $1 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.
Is GLM-4.5 or Sonar better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 35.7 in the Noometry coding category.
Which has the bigger context window?
GLM-4.5 does, with 131K tokens against 128K.
How many benchmarks do GLM-4.5 and Sonar share?
0 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Sonar has 7.