Model comparison
Gemini 3.6 Flash vs GLM-5
Head-to-head evidence from 9 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 3.6 Flash unranked (Not scored); GLM-5 #28 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 3.6 Flash and GLM-5 share 9 comparable benchmark results. 1 of 8 categories are comparable. 10 results are unique to Gemini 3.6 Flash; 40 to GLM-5.
Updated July 21, 2026- Shared results
- 9
- Gemini 3.6 Flash only
- 10
- GLM-5 only
- 40
- Comparable categories
- 1 / 8
Treat this as a split decision. Gemini 3.6 Flash makes more sense if agentic is the priority or you need the larger 1M context window; GLM-5 is the better fit if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 9 shared benchmark results across 3 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Gemini 3.6 Flash 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.
Gemini 3.6 Flash is also the more expensive model on tokens at $1.50 input / $7.50 output per 1M tokens, versus $1.00 input / $3.20 output per 1M tokens for GLM-5. That is roughly 2.3x on output cost alone. Gemini 3.6 Flash 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. Gemini 3.6 Flash 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 3.6 Flash | Δ | GLM-5 |
|---|---|---|---|
| Agentic | Gemini 3.6 Flash83.0 | Margin← 26.8 | GLM-556.2 |
| Coding | Gemini 3.6 FlashNot measured | MarginNo overlap | GLM-566.3 |
| Reasoning | Gemini 3.6 FlashNot measured | MarginNo overlap | GLM-560.8 |
| Knowledge | Gemini 3.6 FlashNot measured | MarginNo overlap | GLM-566.4 |
| Math | Gemini 3.6 FlashNot measured | MarginNo overlap | GLM-556.3 |
| Multilingual | Gemini 3.6 FlashNot measured | MarginNo overlap | GLM-583.1 |
| Inst. Following | Gemini 3.6 FlashNot measured | MarginNo overlap | GLM-592.6 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 3.6 Flash | GLM-5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3.6 Flash$1.5 input / $7.5 output | GLM-5$1 input / $3.2 output | GLM-5 has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3.6 FlashNot available | GLM-574 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 3.6 FlashNot available | GLM-51.64 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 3.6 Flash1M | GLM-5200K | Gemini 3.6 Flash lists the larger context window. |
Benchmark Deep Dive
AgenticGemini 3.6 Flash wins20 benchmarks
| Benchmark | Gemini 3.6 Flash | GLM-5 | Result |
|---|---|---|---|
| OSWorld-VerifiedSource | 83% | — | Not comparable |
| GDPval-AASource | 1421 | — | Not comparable |
| AA Agentic IndexSource | 38.7% | — | Not comparable |
| GDPval-AASource | 46.1% | — | Not comparable |
| AA BriefcaseSource | 961 | — | Not comparable |
| AA Tau3 BankingSource | 24.5% | — | Not comparable |
| aaTerminalBench21Source | 77.5% | — | 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 |
| 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 |
Coding9 benchmarks
| Benchmark | Gemini 3.6 Flash | GLM-5 | Result |
|---|---|---|---|
| deepSweSource | 49% | — | Not comparable |
| AA Coding IndexSource | 69.2% | — | Not comparable |
| AA-SciCodeSource | 52.7% | 46.2% | Gemini 3.6 Flash leads |
| SWE-bench VerifiedSource | — | 77.8% | Not comparable |
| 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
Knowledge12 benchmarks
| Benchmark | Gemini 3.6 Flash | GLM-5 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 50.1% | 39.5% | Gemini 3.6 Flash leads |
| AA-GPQA DiamondSource | 92.8% | 82.0% | Gemini 3.6 Flash leads |
| AA-HLESource | 38.3% | 27.2% | Gemini 3.6 Flash leads |
| AA-Omniscience IndexSource | 23.5% | 2.0% | Gemini 3.6 Flash leads |
| AA-Omniscience AccuracySource | 50.2% | 26.9% | Gemini 3.6 Flash leads |
| AA-Omniscience Hallucination RateSource | 53.5% | 34.0% | GLM-5 leads |
| 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 |
Math8 benchmarks
| Benchmark | Gemini 3.6 Flash | 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
Multimodal2 benchmarks
Frequently Asked Questions (2)
Which is better, Gemini 3.6 Flash or GLM-5?
Gemini 3.6 Flash 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 agentic tasks, Gemini 3.6 Flash or GLM-5?
Gemini 3.6 Flash has the edge for agentic tasks in this comparison, averaging 83 versus 56.2. GLM-5 stays close enough that the answer can still flip depending on your workload.
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