Model comparison
GLM-5 vs Sonar
GLM-5 is the stronger model overall, scoring 45.9 to 37.8 on the Noometry Index. Sonar costs 1.6× less per token, which makes it the better buy when GLM-5's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
PerplexitySummary
- The widest gap is in coding, where GLM-5 leads 49.0 to 35.1.
- Sonar is cheaper at $1 / $1 per million input/output tokens, against $1 / $3.20 for GLM-5.
- GLM-5 accepts more context: 205K tokens versus 128K.
- GLM-5 has downloadable open weights; the other is API-only.
Side by side
| GLM-5 | Sonar | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Perplexity |
| Noometry Index | 45.9 | 37.8 |
| Released | 2026-02-11 | 2024-01-01 |
| Weights | Open | Proprietary |
| Context window | 205K | 128K |
| Max output | 131K | 4K |
| Input $ / M tokens | $1 | $1 |
| Output $ / M tokens | $3.20 | $1 |
| Results tracked | 45 | 7 |
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Category by category
Coding GLM-5 leads
GLM-5: 49.0 (#47), Sonar: 35.1 (#217)
| Benchmark | GLM-5 | Sonar |
|---|---|---|
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
| LiveBench Coding | — | 35.1% |
| LMArena Coding | 1461 | — |
| ALE-Bench | 765.62 | — |
Agentic & Tool Use Not comparable
GLM-5: 30.9 (#65), Sonar: —
| Benchmark | GLM-5 | Sonar |
|---|---|---|
| Terminal-Bench | 52.4% | — |
| τ²-bench Airline | 82.5% | — |
| τ²-bench Banking | 9.8% | — |
| τ²-bench Retail | 73.7% | — |
| τ²-bench Telecom | 86.8% | — |
| Vending-Bench 2 | 4,432 | — |
Reasoning GLM-5 leads
GLM-5: 27.6 (#100), Sonar: 20.3 (#221)
| Benchmark | GLM-5 | Sonar |
|---|---|---|
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | 75% | — |
| NYT Connections (extended) | 74.8% | — |
| ARC-AGI-1 | 44.7% | — |
| Chess Puzzles | 10% | — |
| LiveBench Reasoning | — | 46.3% |
| LMArena Hard Prompts | 1451 | — |
| LiveBench Data Analysis | — | 37.9% |
| Epoch Capabilities Index | 145.84 | — |
| ForecastBench | 61 | — |
| LiveBench | — | 46.9% |
Math GLM-5 leads
GLM-5: 44.8 (#66), Sonar: 31.3 (#197)
| Benchmark | GLM-5 | Sonar |
|---|---|---|
| MathArena Final-Answer Competitions | 65.7% | — |
| OTIS Mock AIME 2024-2025 | 80% | — |
| LiveBench Math | — | 41.6% |
| LMArena Math | 1440 | — |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Not comparable
GLM-5: 52.2 (#59), Sonar: —
| Benchmark | GLM-5 | Sonar |
|---|---|---|
| GPQA Diamond | 87.8% | — |
| Vectara Hallucination Rate | 10.1% | — |
| LMArena Expert | 1454 | — |
Multilingual Not comparable
GLM-5: 53.9 (#57), Sonar: —
| Benchmark | GLM-5 | Sonar |
|---|---|---|
| LMArena Non-English | 1430 | — |
| LMArena Chinese | 1511 | — |
| LMArena French | 1455 | — |
| LMArena German | 1445 | — |
| LMArena Japanese | 1416 | — |
| LMArena Korean | 1421 | — |
| LMArena Russian | 1436 | — |
| LMArena Spanish | 1452 | — |
Instruction Following GLM-5 leads
GLM-5: 75.4 (#64), Sonar: 71.5 (#146)
| Benchmark | GLM-5 | Sonar |
|---|---|---|
| LiveBench Instruction Following | — | 76.2% |
| LMArena Instruction Following | 1427 | — |
Long Context Not comparable
GLM-5: 44.6 (#58), Sonar: —
| Benchmark | GLM-5 | Sonar |
|---|---|---|
| CL-bench | 18.7% | — |
| LMArena Longer Query | 1446 | — |
Writing & Preference GLM-5 leads
GLM-5: 66.2 (#38), Sonar: 52.6 (#166)
| Benchmark | GLM-5 | Sonar |
|---|---|---|
| LMArena Text | 1446 | — |
| LMArena Creative Writing | 1438 | — |
| EQ-Bench Creative Writing | 1601 | — |
| LMArena Multi-Turn | 1456 | — |
| LiveBench Language | — | 44.1% |
Frequently asked questions
Is GLM-5 better than Sonar?
GLM-5 is the stronger model overall, scoring 45.9 to 37.8 on the Noometry Index. Sonar costs 1.6× less per token, which makes it the better buy when GLM-5's lead doesn't matter for your workload.
Which is cheaper, GLM-5 or Sonar?
Sonar is cheaper. It lists at $1 per million input tokens and $1 per million output tokens; GLM-5 lists at $1 and $3.20.
Is GLM-5 or Sonar better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 35.1 in the Noometry coding category.
Which has the bigger context window?
GLM-5 does, with 205K tokens against 128K.
How many benchmarks do GLM-5 and Sonar share?
0 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Sonar has 7.