Model comparison
Claude 3.5 Sonnet vs GLM-5
Head-to-head evidence from 4 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude 3.5 Sonnet #132 (Estimated); GLM-5 #28 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude 3.5 Sonnet and GLM-5 share 4 comparable benchmark results. 3 of 8 categories are comparable. 0 results are unique to Claude 3.5 Sonnet; 45 to GLM-5.
Updated July 22, 2026- Shared results
- 4
- Claude 3.5 Sonnet only
- 0
- GLM-5 only
- 45
- Comparable categories
- 3 / 8
Pick GLM-5 if you want the stronger benchmark profile. Claude 3.5 Sonnet only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Confidence note. This is a partial-evidence comparison with 4 shared benchmark results across 3 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GLM-5 is clearly ahead on the BenchAlign aggregate, 66.06 to 47.74. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5's sharpest advantage is in mathematics, where it averages 56.3 against 1.6. The single biggest benchmark swing on the page is SWE-bench Verified, 49% to 77.8%.
Claude 3.5 Sonnet is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $1.00 input / $3.20 output per 1M tokens for GLM-5. That is roughly 4.7x on output cost alone.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Claude 3.5 Sonnet | Δ | GLM-5 |
|---|---|---|---|
| Math | Claude 3.5 Sonnet1.6 | Margin→ 54.7 | GLM-556.3 |
| Coding | Claude 3.5 Sonnet49.0 | Margin→ 17.3 | GLM-566.3 |
| Knowledge | Claude 3.5 Sonnet59.4 | Margin→ 7.0 | GLM-566.4 |
| Agentic | Claude 3.5 SonnetNot measured | MarginNo overlap | GLM-556.2 |
| Reasoning | Claude 3.5 SonnetNot measured | MarginNo overlap | GLM-560.8 |
| Multilingual | Claude 3.5 SonnetNot measured | MarginNo overlap | GLM-583.1 |
| Inst. Following | Claude 3.5 SonnetNot measured | MarginNo overlap | GLM-592.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 49%B 77.8%Winner: GLM-5Δ 28.8SWE-bench Verified: Claude 3.5 Sonnet scored 49%; GLM-5 scored 77.8%. GLM-5 wins this benchmark. - Source ↗
GPQA
KnowledgeA 59.4%B 86%Winner: GLM-5Δ 26.6GPQA: Claude 3.5 Sonnet scored 59.4%; GLM-5 scored 86%. GLM-5 wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 2.069%B 16.434%Winner: GLM-5Δ 14.4FrontierMath v2 (Tiers 1-3): Claude 3.5 Sonnet scored 2.069%; GLM-5 scored 16.434%. GLM-5 wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 0.000%B 2.100%Winner: GLM-5Δ 2.1FrontierMath v2 (Tier 4): Claude 3.5 Sonnet scored 0.000%; GLM-5 scored 2.100%. GLM-5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude 3.5 Sonnet | GLM-5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude 3.5 Sonnet$3 input / $15 output | GLM-5$1 input / $3.2 output | GLM-5 has the lower combined listed price. |
| Generation speedtokens per second | Claude 3.5 SonnetNot available | GLM-574 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude 3.5 SonnetNot available | GLM-51.64 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude 3.5 Sonnet200K | GLM-5200K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic13 benchmarks
| Benchmark | Claude 3.5 Sonnet | GLM-5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 56.2% | Not comparable |
| Claw-EvalSource | — | 57.7% | Not comparable |
| QwenClawBenchSource | — | 54.1% | Not comparable |
| τ³-bench resultsSource | — | 65.6% | Not comparable |
| DeepPlanningSource | — | 14.6% | Not comparable |
| ToolathlonSource | — | 38% | Not comparable |
| MCP AtlasSource | — | 31.1% | Not comparable |
| MCP-TasksSource | — | 60.8% | Not comparable |
| WideResearchSource | — | 69.8% | Not comparable |
| τ²-bench resultsSource | — | 98.2% | Not comparable |
| CyberGymSource | — | 43.2% | Not comparable |
| APEX-Agents-AASource | — | 14.5% | Not comparable |
| Gert LabsSource | — | 50.99% | Not comparable |
CodingGLM-5 wins7 benchmarks
| Benchmark | Claude 3.5 Sonnet | GLM-5 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 49% | 77.8% | GLM-5 leads |
| SWE-bench Verified*Source | — | 72.8% | Not comparable |
| SWE-bench ProSource | — | 55.1% | Not comparable |
| SWE MultilingualSource | — | 73.3% | Not comparable |
| SWE-RebenchSource | — | 62.8% | Not comparable |
| React Native EvalsSource | — | 74.8% | Not comparable |
| AA-SciCodeSource | — | 46.2% | Not comparable |
Reasoning4 benchmarks
KnowledgeGLM-5 wins12 benchmarks
| Benchmark | Claude 3.5 Sonnet | GLM-5 | Result |
|---|---|---|---|
| GPQASource | 59.4% | 86% | GLM-5 leads |
| GPQA-DSource | — | 86.0% | Not comparable |
| SuperGPQASource | — | 66.8% | Not comparable |
| MMLU-ProSource | — | 85.7% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 85.8% | Not comparable |
| HLESource | — | 50.4% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 39.5% | Not comparable |
| AA-GPQA DiamondSource | — | 82.0% | Not comparable |
| AA-HLESource | — | 27.2% | Not comparable |
| AA-Omniscience IndexSource | — | 2.0% | Not comparable |
| AA-Omniscience AccuracySource | — | 26.9% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 34.0% | Not comparable |
MathGLM-5 wins8 benchmarks
| Benchmark | Claude 3.5 Sonnet | GLM-5 | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 2.069% | 16.434% | GLM-5 leads |
| FrontierMath v2 (Tier 4)Source | 0.000% | 2.100% | GLM-5 leads |
| AIME26Source | — | 95.8% | Not comparable |
| AIME25 (Arcee)Source | — | 93.3% | Not comparable |
| HMMT Feb 2025Source | — | 97.5% | Not comparable |
| HMMT Nov 2025Source | — | 96.9% | Not comparable |
| HMMT Feb 2026Source | — | 86.4% | Not comparable |
| MMAnswerBenchSource | — | 82.5% | Not comparable |
Multilingual2 benchmarks
Multimodal1 benchmarks
| Benchmark | Claude 3.5 Sonnet | GLM-5 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1278 | Not comparable |
Frequently Asked Questions (4)
Which is better, Claude 3.5 Sonnet or GLM-5?
GLM-5 is ahead on BenchLM's BenchAlign leaderboard, 66.06 to 47.74. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 49% and 77.8%.
Which is better for knowledge tasks, Claude 3.5 Sonnet or GLM-5?
GLM-5 has the edge for knowledge tasks in this comparison, averaging 66.4 versus 59.4. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, Claude 3.5 Sonnet or GLM-5?
GLM-5 has the edge for coding in this comparison, averaging 66.3 versus 49. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, Claude 3.5 Sonnet or GLM-5?
GLM-5 has the edge for math in this comparison, averaging 56.3 versus 1.6. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
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