Model comparison
Gemini 2.5 Pro vs GLM-5
Head-to-head evidence from 18 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 2.5 Pro #70 (Supported); GLM-5 #28 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 2.5 Pro and GLM-5 share 18 comparable benchmark results. 3 of 8 categories are comparable. 6 results are unique to Gemini 2.5 Pro; 31 to GLM-5.
Updated July 20, 2026- Shared results
- 18
- Gemini 2.5 Pro only
- 6
- GLM-5 only
- 31
- Comparable categories
- 3 / 8
Pick GLM-5 if you want the stronger benchmark profile. Gemini 2.5 Pro only becomes the better choice if you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 7 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 57.25. 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 11.6. The single biggest benchmark swing on the page is HLE, 18.8% to 50.4%.
Gemini 2.5 Pro is also the more expensive model on tokens at $1.25 input / $10.00 output per 1M tokens, versus $1.00 input / $3.20 output per 1M tokens for GLM-5. That is roughly 3.1x on output cost alone. Gemini 2.5 Pro gives you the larger context window at 1M, compared with 200K for GLM-5.
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 | Gemini 2.5 Pro | Δ | GLM-5 |
|---|---|---|---|
| Math | Gemini 2.5 Pro11.6 | Margin→ 44.7 | GLM-556.3 |
| Knowledge | Gemini 2.5 Pro27.4 | Margin→ 39.0 | GLM-566.4 |
| Coding | Gemini 2.5 Pro63.8 | Margin→ 2.5 | GLM-566.3 |
| Agentic | Gemini 2.5 ProNot measured | MarginNo overlap | GLM-556.2 |
| Reasoning | Gemini 2.5 ProNot measured | MarginNo overlap | GLM-560.8 |
| Multilingual | Gemini 2.5 ProNot measured | MarginNo overlap | GLM-583.1 |
| Inst. Following | Gemini 2.5 ProNot measured | MarginNo overlap | GLM-592.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 18.8%B 50.4%Winner: GLM-5Δ 31.6HLE: Gemini 2.5 Pro scored 18.8%; GLM-5 scored 50.4%. GLM-5 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 63.8%B 77.8%Winner: GLM-5Δ 14SWE-bench Verified: Gemini 2.5 Pro scored 63.8%; GLM-5 scored 77.8%. GLM-5 wins this benchmark. - Source ↗
GPQA
KnowledgeA 83%B 86%Winner: GLM-5Δ 3GPQA: Gemini 2.5 Pro scored 83%; GLM-5 scored 86%. GLM-5 wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 14.138%B 16.434%Winner: GLM-5Δ 2.3FrontierMath v2 (Tiers 1-3): Gemini 2.5 Pro scored 14.138%; GLM-5 scored 16.434%. GLM-5 wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 4.167%B 2.100%Winner: Gemini 2.5 ProΔ 2.1FrontierMath v2 (Tier 4): Gemini 2.5 Pro scored 4.167%; GLM-5 scored 2.100%. Gemini 2.5 Pro wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 2.5 Pro | GLM-5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 2.5 Pro$1.25 input / $10 output | GLM-5$1 input / $3.2 output | GLM-5 has the lower combined listed price. |
| Generation speedtokens per second | Gemini 2.5 Pro117 tok/s | GLM-574 tok/s | Gemini 2.5 Pro has the higher measured throughput. |
| First-answer latencyseconds to first token | Gemini 2.5 Pro21.19 s | GLM-51.64 s | GLM-5 reaches the first token sooner. |
| Context windowmaximum listed tokens | Gemini 2.5 Pro1M | GLM-5200K | Gemini 2.5 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic16 benchmarks
| Benchmark | Gemini 2.5 Pro | GLM-5 | Result |
|---|---|---|---|
| AA Agentic IndexSource | 7.1% | — | Not comparable |
| τ²-bench resultsSource | 54.1% | 98.2% | GLM-5 leads |
| Gert LabsSource | 42.01% | 50.99% | GLM-5 leads |
| GDPval-AASource | 8.3% | — | Not comparable |
| GDPval-AASource | 665 | — | Not comparable |
| 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 |
| CyberGymSource | — | 43.2% | Not comparable |
| APEX-Agents-AASource | — | 14.5% | Not comparable |
CodingGLM-5 wins9 benchmarks
| Benchmark | Gemini 2.5 Pro | GLM-5 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 63.8% | 77.8% | GLM-5 leads |
| Vibe Code BenchSource | 0.40% | — | Not comparable |
| AA Coding IndexSource | 33.3% | — | Not comparable |
| AA-SciCodeSource | 42.8% | 46.2% | 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 |
Reasoning4 benchmarks
KnowledgeGLM-5 wins12 benchmarks
| Benchmark | Gemini 2.5 Pro | GLM-5 | Result |
|---|---|---|---|
| GPQASource | 83% | 86% | GLM-5 leads |
| HLESource | 18.8% | 50.4% | GLM-5 leads |
| Artificial Analysis Intelligence IndexSource | 25.8% | 39.5% | GLM-5 leads |
| AA-GPQA DiamondSource | 84.4% | 82.0% | Gemini 2.5 Pro leads |
| AA-HLESource | 21.1% | 27.2% | GLM-5 leads |
| AA-Omniscience IndexSource | -14.3% | 2.0% | GLM-5 leads |
| AA-Omniscience AccuracySource | 39.0% | 26.9% | Gemini 2.5 Pro leads |
| AA-Omniscience Hallucination RateSource | 87.4% | 34.0% | 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 |
MathGLM-5 wins8 benchmarks
| Benchmark | Gemini 2.5 Pro | GLM-5 | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 14.138% | 16.434% | GLM-5 leads |
| FrontierMath v2 (Tier 4)Source | 4.167% | 2.100% | Gemini 2.5 Pro 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
Multimodal2 benchmarks
Frequently Asked Questions (4)
Which is better, Gemini 2.5 Pro or GLM-5?
GLM-5 is ahead on BenchLM's BenchAlign leaderboard, 66.06 to 57.25. The biggest single separator in this matchup is HLE, where the scores are 18.8% and 50.4%.
Which is better for knowledge tasks, Gemini 2.5 Pro or GLM-5?
GLM-5 has the edge for knowledge tasks in this comparison, averaging 66.4 versus 27.4. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, Gemini 2.5 Pro or GLM-5?
GLM-5 has the edge for coding in this comparison, averaging 66.3 versus 63.8. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, Gemini 2.5 Pro or GLM-5?
GLM-5 has the edge for math in this comparison, averaging 56.3 versus 11.6. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
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