GLM 4.7 Flash vs GPT-6 Luna
GPT-6 Luna leads GLM 4.7 Flash on the Artificial Analysis Intelligence Index, 38.1 to 14.9, and GLM 4.7 Flash costs 1.3x less per output token ($0.40 vs $0.50 per million). Updated October 21, 2026; 39 benchmarks have a result for both.
GLM 4.7 Flash or GPT-6 Luna: which to pick
Only GPT-6 Luna has a coding score, 57.3 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding.
Pick GLM 4.7 Flash for output tokens 1.3x cheaper ($0.40 vs $0.50 per million).
- Shared results
- 39
- GLM 4.7 Flash only
- 4
- GPT-6 Luna only
- 64
- Like-for-like categories
- 7 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only GPT-6 Luna has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-6 Luna
GPT-6 Luna leads, 38.1 against 14.9.
Same board, both measured
Web design
Design Arena: websites
GPT-6 Luna
GPT-6 Luna leads, 1272 against 1194.
Same board, both measured
General
Vals Index
No call
Only GPT-6 Luna has a Vals Index result, 52.3%.
Directional only
Long documents
Listed context window
GPT-6 Luna
GPT-6 Luna takes 1.05M tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.7 Flash
GLM 4.7 Flash $0.0003, GPT-6 Luna $0.0003 per turn.
List prices
At a glance
- Coding index
- GLM 4.7 Flash not benchmarked, GPT-6 Luna 57.3 from 5 benchmarks.
- Widest category
- Intelligence, 23.2 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): GLM 4.7 Flash 41.7% against GPT-6 Luna 83.3%, 41.7 points apart on a 0 to 100 scale.
- Output price
- GLM 4.7 Flash $0.40 against GPT-6 Luna $0.50 per million output tokens, 1.3x apart.
- Context window
- GLM 4.7 Flash takes 200K tokens, GPT-6 Luna 1.05M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GLM 4.7 Flash | Bars | GPT-6 Luna | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 7 | ||
| General | 0 | 17 | ||
| All shared boards | 0 | 39 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GLM 4.7 Flash | GPT-6 Luna | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 84.5% | Only GPT-6 Luna measured |
| LMArena WebDev | Not measured | 1578 | Only GPT-6 Luna measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 13.6% | Only GPT-6 Luna measured |
| Vibe Code Bench (Vals AI) | Not measured | 81.7% | Only GPT-6 Luna measured |
| Code migration (Vals AI) | Not measured | 42.5% | Only GPT-6 Luna measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only GPT-6 Luna measured |
| IOI (Vals AI) | Not measured | 55.6% | Only GPT-6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 73.0% | Only GPT-6 Luna measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 37.5% | Only GPT-6 Luna measured |
| CyberBench (Vals AI) | Not measured | 76.3% | Only GPT-6 Luna measured |
| SciCode | Not measured | 54.6% | Only GPT-6 Luna measured |
| Terminal-Bench Hard (Artificial Analysis run) | 22.0% | Not measured | Only GLM 4.7 Flash measured |
| FrontierCode | Not measured | 42.4% | Only GPT-6 Luna measured |
| ALE-Bench | Not measured | 1576.9 | Only GPT-6 Luna measured |
| LMArena Text: coding | 1382 | 1437 | GPT-6 Luna |
| LMArena Text: software and IT | 1389 | 1423 | GPT-6 Luna |
| LMArena WebDev: React | Not measured | 1573 | Only GPT-6 Luna measured |
| LMArena WebDev: HTML | Not measured | 1595 | Only GPT-6 Luna measured |
| LMArena WebDev: from an image | Not measured | 1571 | Only GPT-6 Luna measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.7 Flash | GPT-6 Luna | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.9 | 38.1 | GPT-6 Luna |
| Epoch Capabilities Index | Not measured | 156.8 | Only GPT-6 Luna measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | GLM 4.7 Flash | GPT-6 Luna | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1191 | Only GPT-6 Luna measured |
| Design Arena: agents building full-stack apps | Not measured | 1158 | Only GPT-6 Luna measured |
| Design Arena: agents building mobile apps | Not measured | 1128 | Only GPT-6 Luna measured |
| LiveBench research | Not measured | 43.5% | Only GPT-6 Luna measured |
| LiveBench browser | Not measured | 72.0% | Only GPT-6 Luna measured |
| LiveBench long agentic | Not measured | 48.1% | Only GPT-6 Luna measured |
| SREBench (Vals AI) | Not measured | 2.7% | Only GPT-6 Luna measured |
| Finance Agent (Vals AI) | Not measured | 49.9% | Only GPT-6 Luna measured |
| Tax Agent Bench (Vals AI) | Not measured | 19.9% | Only GPT-6 Luna measured |
| Legal Research Bench (Vals AI) | Not measured | 30.3% | Only GPT-6 Luna measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 4.2% | Only GPT-6 Luna measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 68.5% | Only GPT-6 Luna measured |
| BioMysteryBench (Vals AI) | Not measured | 61.5% | Only GPT-6 Luna measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 4.3% | Only GPT-6 Luna measured |
| Vals Science Index | Not measured | 28.4% | Only GPT-6 Luna measured |
| τ²-Bench Telecom | 98.8% | Not measured | Only GLM 4.7 Flash measured |
| APEX-Agents | Not measured | 44.3% | Only GPT-6 Luna measured |
| SpireClimb | Not measured | 0.0% | Only GPT-6 Luna measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | GLM 4.7 Flash | GPT-6 Luna | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 81.8% | Only GPT-6 Luna measured |
| MysteryMechanism (Vals AI) | Not measured | 19.4% | Only GPT-6 Luna measured |
| GPQA Diamond (Artificial Analysis run) | 58.1% | Not measured | Only GLM 4.7 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 7.6% | 38.5% | GPT-6 Luna |
| GPQA Diamond (Epoch AI run) | 60.5% | 90.5% | GPT-6 Luna |
| ARC-AGI | Not measured | 86.7% | Only GPT-6 Luna measured |
| ARC-AGI-2 | Not measured | 59.3% | Only GPT-6 Luna measured |
| Chess puzzles | Not measured | 36.0% | Only GPT-6 Luna measured |
| Mystery game puzzles | Not measured | 7.0% | Only GPT-6 Luna measured |
| LMArena Text: hard prompts | 1356 | 1410 | GPT-6 Luna |
| LMArena Text: expert | 1357 | 1442 | GPT-6 Luna |
| LMArena Text: hard prompts in English | 1369 | 1410 | GPT-6 Luna |
| LMArena Vision: diagrams | Not measured | 1245 | Only GPT-6 Luna measured |
| LMArena Vision: homework | Not measured | 1261 | Only GPT-6 Luna measured |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GLM 4.7 Flash | GPT-6 Luna | Leader |
|---|---|---|---|
| OTIS Mock AIME | 58.3% | 98.9% | GPT-6 Luna |
| FrontierMath, tiers 1 to 3 | Not measured | 78.9% | Only GPT-6 Luna measured |
| FrontierMath, tier 4 | Not measured | 56.1% | Only GPT-6 Luna measured |
| ProofBench | Not measured | 64.0% | Only GPT-6 Luna measured |
| LMArena Text: math | 1355 | 1409 | GPT-6 Luna |
| LMArena Text: mathematical work | 1369 | 1427 | GPT-6 Luna |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GLM 4.7 Flash | GPT-6 Luna | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 44.7% | Only GPT-6 Luna measured |
| SimpleQA Verified | Not measured | 41.4% | Only GPT-6 Luna measured |
| LMArena Text: science | 1358 | 1386 | GPT-6 Luna |
| LMArena Text: medicine and healthcare | 1343 | 1352 | GPT-6 Luna |
| LMArena Text: legal and government | 1357 | 1400 | GPT-6 Luna |
| LMArena Text: business and finance | 1343 | 1388 | GPT-6 Luna |
| FACTS Benchmark Suite | Not measured | 63.3% | Only GPT-6 Luna measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | GLM 4.7 Flash | GPT-6 Luna | Leader |
|---|---|---|---|
| Design Arena: websites | 1194 | 1272 | GPT-6 Luna |
| Design Arena: UI components | 1208 | 1297 | GPT-6 Luna |
| Design Arena: game dev | 1135 | 1260 | GPT-6 Luna |
| Design Arena: data viz | 1123 | 1215 | GPT-6 Luna |
| Design Arena: 3D | 1121 | 1217 | GPT-6 Luna |
| Design Arena: all code categories | 1178 | 1271 | GPT-6 Luna |
| Design Arena: SVG | 1038 | 1251 | GPT-6 Luna |
| Design Arena: ASCII art | Not measured | 1153 | Only GPT-6 Luna measured |
| LiveBench design | Not measured | 82.5% | Only GPT-6 Luna measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
| Benchmark | GLM 4.7 Flash | GPT-6 Luna | Leader |
|---|---|---|---|
| Vals Index | Not measured | 52.3% | Only GPT-6 Luna measured |
| LiveBench data analysis | Not measured | 73.4% | Only GPT-6 Luna measured |
| Public Benefits Bench (Vals AI) | Not measured | 57.6% | Only GPT-6 Luna measured |
| SAGE (Vals AI) | Not measured | 48.1% | Only GPT-6 Luna measured |
| MedScribe (Vals AI) | Not measured | 83.7% | Only GPT-6 Luna measured |
| IFBench | 60.8% | Not measured | Only GLM 4.7 Flash measured |
| Long context reasoning (AA-LCR) | 41.7% | 83.3% | GPT-6 Luna |
| DTBench | Not measured | 90.1% | Only GPT-6 Luna measured |
| LMCA | Not measured | 44.5% | Only GPT-6 Luna measured |
| Furniture assembly | Not measured | 44.2% | Only GPT-6 Luna measured |
| LMArena Text | 1351 | 1389 | GPT-6 Luna |
| LMArena Text: instruction following | 1327 | 1408 | GPT-6 Luna |
| LMArena Text: creative writing | 1296 | 1363 | GPT-6 Luna |
| LMArena Vision | Not measured | 1216 | Only GPT-6 Luna measured |
| LMArena Text: English | 1373 | 1393 | GPT-6 Luna |
| LMArena Text: non-English | 1330 | 1381 | GPT-6 Luna |
| LMArena Text: Chinese | 1403 | 1427 | GPT-6 Luna |
| LMArena Text: German | 1336 | 1376 | GPT-6 Luna |
| LMArena Text: Japanese | Not measured | 1369 | Only GPT-6 Luna measured |
| LMArena Text: Korean | 1283 | 1359 | GPT-6 Luna |
| LMArena Text: French | 1332 | 1408 | GPT-6 Luna |
| LMArena Text: Spanish | 1350 | 1391 | GPT-6 Luna |
| LMArena Text: Russian | 1333 | 1392 | GPT-6 Luna |
| LMArena Text: Polish | 1291 | 1383 | GPT-6 Luna |
| LMArena Text: multi-turn | 1342 | 1392 | GPT-6 Luna |
| LMArena Text: longer queries | 1345 | 1408 | GPT-6 Luna |
| LMArena Text: writing and language | 1320 | 1384 | GPT-6 Luna |
| LMArena Text: entertainment and media | 1304 | 1364 | GPT-6 Luna |
| LMArena Vision: English | Not measured | 1204 | Only GPT-6 Luna measured |
| LMArena Vision: Chinese | Not measured | 1266 | Only GPT-6 Luna measured |
| LMArena Vision: reading text | Not measured | 1225 | Only GPT-6 Luna measured |
| LMArena Vision: creative writing | Not measured | 1205 | Only GPT-6 Luna measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.7 Flash | GPT-6 Luna | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
GLM 4.7 Flash costs less
Repository review
50K input + 3K output tokens
GLM 4.7 Flash costs less
Agent loop
200K input + 10K output tokens
GLM 4.7 Flash costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Z.ai GLM 4.7 Flash | OpenAI GPT-6 Luna |
|---|---|---|
| Maker | Z.ai | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | January 19, 2026 | September 22, 2026 |
| Context window | 200K | 1.05M |
| Input $/Mtok | $0.0653 | $0.10 |
| Output $/Mtok | $0.40 | $0.50 |
| Coding index | Not benchmarked | 57.3 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 4.7 Flash better than GPT-6 Luna for coding?
Only GPT-6 Luna has a coding score, 57.3 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for output tokens 1.3x cheaper ($0.40 vs $0.50 per million).
Which is cheaper, GLM 4.7 Flash or GPT-6 Luna?
GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; GPT-6 Luna costs $0.10 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 4.7 Flash or GPT-6 Luna?
GPT-6 Luna, with 1.05M tokens against 200K.
How many benchmarks is the GLM 4.7 Flash vs GPT-6 Luna comparison based on?
39 benchmarks have a result for both models as of October 21, 2026. GLM 4.7 Flash's coding index rests on 0 independent benchmarks and GPT-6 Luna's on 5. Where only one model has a result, the page says so instead of naming a winner.