Compare / head-to-head
GLM-4.6Vvs
GPT-6 Luna
GPT-6 Luna leads 1 of 1 shared benchmark. GPT-6 Luna is 2x cheaper per token. GPT-6 Luna has the larger context window (1.1M tokens).
Benchmarks from cited public sources; pricing from official pages; status from official provider feeds.
Shared benchmarks
0 – 1
GPT-6 Luna leads
Cheaper per token
GPT-6 Luna
2x cheaper, input + output
Larger context
GPT-6 Luna
1.1M tokens
Providers
2 providers
Z.ai · OpenAI
GLM-4.6V
Z.ai · released 2025-12-08
textvisionvideo
GPT-6 Luna
OpenAI · released 2026-09-22
textvision
Quality
Benchmark matrix
1 shared · 16 only GLM-4.6V · 21 only GPT-6 Luna| Benchmark | GLM-4.6V | GPT-6 Luna | Δ | Edge |
|---|---|---|---|---|
| Reported by both · 1 | ||||
| LMArena Elo | 1378.7 ↗ | 1442.9 ↗ | -64.2 | GPT-6 Luna |
| Only GLM-4.6V reports · 16 | ||||
| AndroidWorld | 57% ↗ | not reported | — | — |
| ChartQAPro | 65.5% ↗ | not reported | — | — |
| CharXiv_Val-Reasoning | 63.2% ↗ | not reported | — | — |
| Design2Code | 88.6% ↗ | not reported | — | — |
| LMArena Vision (LMArena) | 1161.5 ↗ | not reported | — | — |
| MathVista | 85.2% ↗ | not reported | — | — |
| MMBench V1.1 | 88.8% ↗ | not reported | — | — |
| MMBrowseComp | 7.6% ↗ | not reported | — | — |
| MMLongBench-Doc | 54.9% ↗ | not reported | — | — |
| MMMU (Val) | 76% ↗ | not reported | — | — |
| MMMU_Pro | 66% ↗ | not reported | — | — |
| MMStar | 75.9% ↗ | not reported | — | — |
| OCRBench | 86.5% ↗ | not reported | — | — |
| OSWorld | 37.2% ↗ | not reported | — | — |
| VideoMMMU | 74.7% ↗ | not reported | — | — |
| WebVoyager | 81% ↗ | not reported | — | — |
| Only GPT-6 Luna reports · 21 | ||||
| GPQA Diamond | not reported | 90.5% ↗epoch run | — | — |
| APEX-Agents (Mercor) | not reported | 44.3% ↗ | — | — |
| Chess Puzzles (Epoch AI run) | not reported | 31% ↗epoch run | — | — |
| DeepSWE v1.1 | not reported | 66.6% ↗ | — | — |
| FrontierMath Tier 4 v2 (Epoch AI run) | not reported | 56.1% ↗epoch run | — | — |
| FrontierMath Tiers 1-3 v2 (Epoch AI run) | not reported | 78.9% ↗epoch run | — | — |
| Furniture Assembly (Epoch AI run) | not reported | 44.2% ↗epoch run | — | — |
| LiveBench Agentic Coding (LiveBench) | not reported | 51.2% ↗ | — | — |
| LiveBench Coding (LiveBench) | not reported | 79% ↗ | — | — |
| LiveBench Data Analysis (LiveBench) | not reported | 73.4% ↗ | — | — |
| LiveBench Instruction Following (LiveBench) | not reported | 55.9% ↗ | — | — |
| LiveBench Language (LiveBench) | not reported | 73.8% ↗ | — | — |
| LiveBench Mathematics (LiveBench) | not reported | 89.1% ↗ | — | — |
| LiveBench Reasoning (LiveBench) | not reported | 81.8% ↗ | — | — |
| LMArena Agent (LMArena) | not reported | 0.0135 ↗ | — | — |
| LMArena WebDev (LMArena) | not reported | 1578.7 ↗ | — | — |
| Mystery Game Puzzles (Epoch AI run) | not reported | 7% ↗epoch run | — | — |
| OTIS Mock AIME 2024-2025 (Epoch AI run) | not reported | 98.9% ↗epoch run | — | — |
| SAGE (Vals AI) | not reported | 48.1% ↗ | — | — |
| SimpleQA Verified | not reported | 41.4% ↗epoch run | — | — |
| Terminal-Bench 4.0 (Vals AI) | not reported | 13.6% ↗ | — | — |
Scores tagged "epoch" or "matharena" are independent runs, used only where the lab has not published its own; ⚠ marks rows MathArena flags as released after the competition. Higher is better on every row. Δ is GLM-4.6V minus GPT-6 Luna in the benchmark's own unit. "Not reported" means the lab has not published that figure; it is not a zero. ↗ opens the source.
Specs & pricing
Side by side
Official pricing pages and model cards| Spec | GLM-4.6V | GPT-6 Luna | Edge |
|---|---|---|---|
| Context window | 128K tokens | 1.1M tokens | GPT-6 Luna |
| Max output | 32K tokens | 128K tokens | GPT-6 Luna |
| Input price / 1M | $0.3 ↗ | $0.1 ↗ | GPT-6 Luna |
| Output price / 1M | $0.9 ↗ | $0.5 ↗ | GPT-6 Luna |
| Cached input / 1M | $0.05 ↗ | $0.01 ↗ | GPT-6 Luna |
| Input + output / 1M Lower is cheaper. List prices; batch, tool and regional fees excluded. | $1.2 | $0.6 | GPT-6 Luna |
| Modalities | text · vision · video | text · vision | GLM-4.6V |
| Released | 2025-12-08 | 2026-09-22 | — |
| Cited benchmark scores | 17 | 22 | — |
Reliability
Provider status
Live from /statusMore matchups
GLM-4.6V vs …
Models sharing the most benchmarksMore matchups
GPT-6 Luna vs …
Models sharing the most benchmarksBuilt by Respan
Which one wins on your data?
Public benchmarks are a starting point. Run GLM-4.6V and GPT-6 Luna on your own prompts with Respan evals, or route to either through one gateway key with automatic failover.