Model comparison
Claude Sonnet 4.5 vs GLM-5
Head-to-head evidence from 7 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Sonnet 4.5 #96 (Estimated); GLM-5 #28 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Sonnet 4.5 and GLM-5 share 7 comparable benchmark results. 5 of 8 categories are comparable. 5 results are unique to Claude Sonnet 4.5; 42 to GLM-5.
Updated July 20, 2026- Shared results
- 7
- Claude Sonnet 4.5 only
- 5
- GLM-5 only
- 42
- Comparable categories
- 5 / 8
Pick GLM-5 if you want the stronger benchmark profile. Claude Sonnet 4.5 only becomes the better choice if knowledge is the priority.
Confidence note. This is a partial-evidence comparison with 7 shared benchmark results across 5 evidence categories; 5 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 53.61. 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 reasoning, where it averages 60.8 against 13.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 50% to 56.2%. Claude Sonnet 4.5 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude Sonnet 4.5 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 Sonnet 4.5 | Δ | GLM-5 |
|---|---|---|---|
| Reasoning | Claude Sonnet 4.513.6 | Margin→ 47.2 | GLM-560.8 |
| Math | Claude Sonnet 4.511.2 | Margin→ 45.1 | GLM-556.3 |
| Knowledge | Claude Sonnet 4.583.4 | Margin← 17.0 | GLM-566.4 |
| Coding | Claude Sonnet 4.577.2 | Margin← 10.9 | GLM-566.3 |
| Agentic | Claude Sonnet 4.555.4 | Margin→ 0.8 | GLM-556.2 |
| Multilingual | Claude Sonnet 4.5Not measured | MarginNo overlap | GLM-583.1 |
| Inst. Following | Claude Sonnet 4.5Not measured | MarginNo overlap | GLM-592.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 50%B 56.2%Winner: GLM-5Δ 6.2Terminal-Bench 2.0: Claude Sonnet 4.5 scored 50%; GLM-5 scored 56.2%. GLM-5 wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 13.495%B 16.434%Winner: GLM-5Δ 2.9FrontierMath v2 (Tiers 1-3): Claude Sonnet 4.5 scored 13.495%; GLM-5 scored 16.434%. GLM-5 wins this benchmark. - Source ↗
GPQA
KnowledgeA 83.4%B 86%Winner: GLM-5Δ 2.6GPQA: Claude Sonnet 4.5 scored 83.4%; GLM-5 scored 86%. GLM-5 wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 4.167%B 2.100%Winner: Claude Sonnet 4.5Δ 2.1FrontierMath v2 (Tier 4): Claude Sonnet 4.5 scored 4.167%; GLM-5 scored 2.100%. Claude Sonnet 4.5 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 77.2%B 77.8%Winner: GLM-5Δ 0.6SWE-bench Verified: Claude Sonnet 4.5 scored 77.2%; GLM-5 scored 77.8%. GLM-5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Sonnet 4.5 | GLM-5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Sonnet 4.5$3 input / $15 output | GLM-5$1 input / $3.2 output | GLM-5 has the lower combined listed price. |
| Generation speedtokens per second | Claude Sonnet 4.5Not available | GLM-574 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Sonnet 4.5Not available | GLM-51.64 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Sonnet 4.5200K | GLM-5200K | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGLM-5 wins16 benchmarks
| Benchmark | Claude Sonnet 4.5 | GLM-5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 50% | 56.2% | GLM-5 leads |
| OSWorld-VerifiedSource | 61.4% | — | Not comparable |
| VITA-BenchSource | 17.0% | — | Not comparable |
| Gert LabsSource | 48.51% | 50.99% | GLM-5 leads |
| JobBenchSource | 27.7% | — | 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 |
CodingClaude Sonnet 4.5 wins7 benchmarks
| Benchmark | Claude Sonnet 4.5 | GLM-5 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 77.2% | 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 |
ReasoningGLM-5 wins5 benchmarks
KnowledgeClaude Sonnet 4.5 wins12 benchmarks
| Benchmark | Claude Sonnet 4.5 | GLM-5 | Result |
|---|---|---|---|
| GPQASource | 83.4% | 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 wins9 benchmarks
| Benchmark | Claude Sonnet 4.5 | GLM-5 | Result |
|---|---|---|---|
| AIME 2025Source | 87% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 13.495% | 16.434% | GLM-5 leads |
| FrontierMath v2 (Tier 4)Source | 4.167% | 2.100% | Claude Sonnet 4.5 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 Sonnet 4.5 | GLM-5 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1222 | 1280 | GLM-5 leads |
Frequently Asked Questions (6)
Which is better, Claude Sonnet 4.5 or GLM-5?
GLM-5 is ahead on BenchLM's BenchAlign leaderboard, 66.06 to 53.61. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 50% and 56.2%.
Which is better for knowledge tasks, Claude Sonnet 4.5 or GLM-5?
Claude Sonnet 4.5 has the edge for knowledge tasks in this comparison, averaging 83.4 versus 66.4. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, Claude Sonnet 4.5 or GLM-5?
Claude Sonnet 4.5 has the edge for coding in this comparison, averaging 77.2 versus 66.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, Claude Sonnet 4.5 or GLM-5?
GLM-5 has the edge for math in this comparison, averaging 56.3 versus 11.2. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
Which is better for reasoning, Claude Sonnet 4.5 or GLM-5?
GLM-5 has the edge for reasoning in this comparison, averaging 60.8 versus 13.6. Claude Sonnet 4.5 stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, Claude Sonnet 4.5 or GLM-5?
GLM-5 has the edge for agentic tasks in this comparison, averaging 56.2 versus 55.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Related Comparisons
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.