Model comparison
Composer 2 vs GLM-5
Head-to-head evidence from 4 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Composer 2 unranked (Not scored); GLM-5 #28 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Composer 2 and GLM-5 share 4 comparable benchmark results. 2 of 8 categories are comparable. 1 result is unique to Composer 2; 45 to GLM-5.
Updated July 18, 2026- Shared results
- 4
- Composer 2 only
- 1
- GLM-5 only
- 45
- Comparable categories
- 2 / 8
Treat this as a split decision. Composer 2 makes more sense if agentic is the priority or you want the cheaper token bill; GLM-5 is the better fit if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 4 shared benchmark results across 2 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Composer 2 and GLM-5 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
GLM-5 is also the more expensive model on tokens at $1.00 input / $3.20 output per 1M tokens, versus $0.50 input / $2.50 output per 1M tokens for Composer 2. Composer 2 is the reasoning model in the pair, while GLM-5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use.
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 | Composer 2 | Δ | GLM-5 |
|---|---|---|---|
| Coding | Composer 258.0 | Margin→ 8.3 | GLM-566.3 |
| Agentic | Composer 261.7 | Margin← 5.5 | GLM-556.2 |
| Reasoning | Composer 2Not measured | MarginNo overlap | GLM-560.8 |
| Knowledge | Composer 2Not measured | MarginNo overlap | GLM-566.4 |
| Math | Composer 2Not measured | MarginNo overlap | GLM-556.3 |
| Multilingual | Composer 2Not measured | MarginNo overlap | GLM-583.1 |
| Inst. Following | Composer 2Not 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 61.7%B 56.2%Winner: Composer 2Δ 5.5Terminal-Bench 2.0: Composer 2 scored 61.7%; GLM-5 scored 56.2%. Composer 2 wins this benchmark. - Source ↗
SWE-Rebench
CodingA 58%B 62.8%Winner: GLM-5Δ 4.8SWE-Rebench: Composer 2 scored 58%; GLM-5 scored 62.8%. GLM-5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Composer 2 | GLM-5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Composer 2$0.5 input / $2.5 output | GLM-5$1 input / $3.2 output | Composer 2 has the lower combined listed price. |
| Generation speedtokens per second | Composer 2Not available | GLM-574 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Composer 2Not available | GLM-51.64 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Composer 2200K | GLM-5200K | Listed context windows are equal. |
Benchmark Deep Dive
AgenticComposer 2 wins13 benchmarks
| Benchmark | Composer 2 | GLM-5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 61.7% | 56.2% | Composer 2 leads |
| 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 wins8 benchmarks
| Benchmark | Composer 2 | GLM-5 | Result |
|---|---|---|---|
| SWE MultilingualSource | 73.7% | 73.3% | Composer 2 leads |
| SWE-RebenchSource | 58% | 62.8% | GLM-5 leads |
| React Native EvalsSource | 96.1% | 74.8% | Composer 2 leads |
| Terminal-Bench 2.0Source | 61.7% | — | Not comparable |
| SWE-bench VerifiedSource | — | 77.8% | Not comparable |
| SWE-bench Verified*Source | — | 72.8% | Not comparable |
| SWE-bench ProSource | — | 55.1% | Not comparable |
| AA-SciCodeSource | — | 46.2% | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | Composer 2 | GLM-5 | Result |
|---|---|---|---|
| GPQASource | — | 86% | Not comparable |
| 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 |
Math8 benchmarks
| Benchmark | Composer 2 | GLM-5 | Result |
|---|---|---|---|
| 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 |
| FrontierMath v2 (Tiers 1-3)Source | — | 16.434% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 2.100% | Not comparable |
Multilingual2 benchmarks
Multimodal1 benchmarks
| Benchmark | Composer 2 | GLM-5 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1280 | Not comparable |
Frequently Asked Questions (3)
Which is better, Composer 2 or GLM-5?
Composer 2 and GLM-5 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for coding, Composer 2 or GLM-5?
GLM-5 has the edge for coding in this comparison, averaging 66.3 versus 58. Inside this category, React Native Evals is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Composer 2 or GLM-5?
Composer 2 has the edge for agentic tasks in this comparison, averaging 61.7 versus 56.2. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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