Model comparison
GLM-5-Turbo vs GPT-5.6 Luna
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: GLM-5-Turbo #24 (Supported); GPT-5.6 Luna #22 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5-Turbo and GPT-5.6 Luna share 9 comparable benchmark results. 0 of 8 categories are comparable. 4 results are unique to GLM-5-Turbo; 32 to GPT-5.6 Luna.
Updated July 23, 2026- Shared results
- 9
- GLM-5-Turbo only
- 4
- GPT-5.6 Luna only
- 32
- Comparable categories
- 0 / 8
Benchmark data for GLM-5-Turbo and GPT-5.6 Luna is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 9 shared benchmark results across 3 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
GPT-5.6 Luna is priced at $1.00 input / $6.00 output per 1M tokens, versus $1.20 input / $4.00 output per 1M tokens for GLM-5-Turbo. GPT-5.6 Luna has the larger context window at 1M, compared with 200K for GLM-5-Turbo.
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 | GLM-5-Turbo | Δ | GPT-5.6 Luna |
|---|---|---|---|
| Agentic | GLM-5-TurboNot measured | MarginNo overlap | GPT-5.6 Luna84.1 |
| Coding | GLM-5-TurboNot measured | MarginNo overlap | GPT-5.6 Luna62.7 |
| Knowledge | GLM-5-TurboNot measured | MarginNo overlap | GPT-5.6 Luna92.3 |
| Math | GLM-5-TurboNot measured | MarginNo overlap | GPT-5.6 Luna73.6 |
| Multimodal | GLM-5-TurboNot measured | MarginNo overlap | GPT-5.6 Luna78.4 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-5-Turbo | GPT-5.6 Luna | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5-Turbo$1.2 input / $4 output | GPT-5.6 Luna$1 input / $6 output | GLM-5-Turbo has the lower combined listed price. |
| Generation speedtokens per second | GLM-5-TurboNot available | GPT-5.6 LunaNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-5-TurboNot available | GPT-5.6 LunaNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-5-Turbo200K | GPT-5.6 Luna1M | GPT-5.6 Luna lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | GLM-5-Turbo | GPT-5.6 Luna | Result |
|---|---|---|---|
| Claw-EvalSource | 55.8% | — | Not comparable |
| τ²-bench resultsSource | 98.5% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 84.7% | Not comparable |
| BrowseCompSource | — | 83.3% | Not comparable |
| OSWorld 2.0Source | — | 45.6% | Not comparable |
| CyberGymSource | — | 77.9% | Not comparable |
| ExploitGymSource | — | 12.4% | Not comparable |
| ToolathlonSource | — | 53.4% | Not comparable |
| AA Agentic IndexSource | — | 45.6% | Not comparable |
| GDPval-AASource | — | 54.2% | Not comparable |
| GDPval-AASource | — | 1584 | Not comparable |
| AA Harvey LABSource | — | 87.9% | Not comparable |
| AA ITBenchSource | — | 40.3% | Not comparable |
| AA Tau3 BankingSource | — | 27.2% | Not comparable |
| AA AutomationBenchSource | — | 42.2% | Not comparable |
| aaTerminalBench21Source | — | 80.9% | Not comparable |
| APEX-Agents-AASource | — | 35.8% | Not comparable |
Coding7 benchmarks
| Benchmark | GLM-5-Turbo | GPT-5.6 Luna | Result |
|---|---|---|---|
| AA-SciCodeSource | 43.6% | 52.5% | GPT-5.6 Luna leads |
| SWE-bench ProSource | — | 62.7% | Not comparable |
| Terminal-Bench 2.0Source | — | 84.7% | Not comparable |
| deepSweSource | — | 67.2% | Not comparable |
| FrontierCode 1.1 ExtendedSource | — | 55.1% | Not comparable |
| cursorBench32Source | — | 61.1% | Not comparable |
| AA Coding IndexSource | — | 71.5% | Not comparable |
Reasoning3 benchmarks
Knowledge10 benchmarks
| Benchmark | GLM-5-Turbo | GPT-5.6 Luna | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 38.1% | 51.2% | GPT-5.6 Luna leads |
| AA-GPQA DiamondSource | 84.7% | 91.1% | GPT-5.6 Luna leads |
| AA-HLESource | 25.4% | 37.2% | GPT-5.6 Luna leads |
| AA-Omniscience IndexSource | -15.1% | -11.2% | GPT-5.6 Luna leads |
| AA-Omniscience AccuracySource | 29.0% | 41.5% | GPT-5.6 Luna leads |
| AA-Omniscience Hallucination RateSource | 62.2% | 90.1% | GLM-5-Turbo leads |
| GPQASource | — | 92.3% | Not comparable |
| GPQA-DSource | — | 92.3% | Not comparable |
| HealthBench ProfessionalSource | — | 55.7% | Not comparable |
| HealthBench HardSource | — | 32.0% | Not comparable |
Math3 benchmarks
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-5-Turbo | GPT-5.6 Luna | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.2% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare GLM-5-Turbo and GPT-5.6 Luna on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for GLM-5-Turbo and GPT-5.6 Luna today?
GLM-5-Turbo: $1.20 input / $4.00 output per 1M tokens GPT-5.6 Luna: $1.00 input / $6.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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