Model comparison
GLM-4.6V vs GPT-5.4 mini
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 41.3 on the Noometry Index. GLM-4.6V costs 3.8× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Last verified . 12 shared benchmarks.
Summary
- They share 12 benchmarks with published results for both. GLM-4.6V scores higher in 0 categories and GPT-5.4 mini in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5.4 mini leads 51.5 to 38.0.
- GLM-4.6V is cheaper at $0.30 / $0.90 per million input/output tokens, against $0.75 / $4.50 for GPT-5.4 mini.
- GPT-5.4 mini accepts more context: 400K tokens versus 128K.
- GLM-4.6V has downloadable open weights; the other is API-only.
Side by side
| GLM-4.6V | GPT-5.4 mini | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 41.3 | 45.0 |
| Released | 2025-12-08 | 2026-03-17 |
| Weights | Open | Proprietary |
| Context window | 128K | 400K |
| Max output | 33K | 128K |
| Input $ / M tokens | $0.30 | $0.75 |
| Output $ / M tokens | $0.90 | $4.50 |
| Results tracked | 12 | 46 |
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Category by category
Coding GPT-5.4 mini leads
GLM-4.6V: 40.9 (#128), GPT-5.4 mini: 45.2 (#72)
| Benchmark | GLM-4.6V | GPT-5.4 mini |
|---|---|---|
| LMArena Coding | 1390 | 1438 |
| FrontierCode | — | 27% |
| LMArena WebDev | — | 1397 |
| SciCode | — | 49.9% |
| WeirdML | — | 60.3% |
| ALE-Bench | — | 1,189 |
Agentic & Tool Use Not comparable
GLM-4.6V: —, GPT-5.4 mini: 29.9 (#81)
| Benchmark | GLM-4.6V | GPT-5.4 mini |
|---|---|---|
| DeepResearch Bench | — | 36.3% |
Reasoning GPT-5.4 mini leads
GLM-4.6V: 27.6 (#115), GPT-5.4 mini: 30.4 (#85)
| Benchmark | GLM-4.6V | GPT-5.4 mini |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1424 |
| ARC-AGI-2 | — | 18.9% |
| Kagi LLM Benchmark | — | 37.9% |
| NYT Connections (extended) | — | 61.8% |
| ARC-AGI-1 | — | 63.7% |
| CritPt | — | 10% |
| Chess Puzzles | — | 24% |
| Thematic Generalization | — | 61.7% |
| Mystery Game Puzzles | — | 11% |
| DTBench | — | 80% |
| LMCA | — | 40.8% |
| Epoch Capabilities Index | — | 148.84 |
| ForecastBench | — | 57 |
Math Not comparable
GLM-4.6V: —, GPT-5.4 mini: 45.5 (#75)
| Benchmark | GLM-4.6V | GPT-5.4 mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 51.2% |
| FrontierMath Tier 4 | — | 9.8% |
| OTIS Mock AIME 2024-2025 | — | 88.9% |
| ProofBench | — | 21% |
| LMArena Math | — | 1419 |
| FrontierMath (Feb 2025 set) | — | 28.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge GPT-5.4 mini leads
GLM-4.6V: 38.0 (#149), GPT-5.4 mini: 51.5 (#67)
| Benchmark | GLM-4.6V | GPT-5.4 mini |
|---|---|---|
| LMArena Expert | 1371 | 1435 |
| GPQA Diamond | — | 86.9% |
| SimpleQA Verified | — | 29.4% |
| Vectara Hallucination Rate | — | 5.5% |
Multimodal GPT-5.4 mini leads
GLM-4.6V: 34.8 (#90), GPT-5.4 mini: 39.7 (#56)
| Benchmark | GLM-4.6V | GPT-5.4 mini |
|---|---|---|
| LMArena Vision | 1164 | 1245 |
Multilingual GPT-5.4 mini leads
GLM-4.6V: 48.6 (#141), GPT-5.4 mini: 51.9 (#96)
| Benchmark | GLM-4.6V | GPT-5.4 mini |
|---|---|---|
| LMArena Non-English | 1359 | 1405 |
| LMArena Chinese | 1425 | 1446 |
| LMArena Russian | 1340 | 1417 |
| LMArena French | — | 1440 |
| LMArena German | — | 1409 |
| LMArena Japanese | — | 1374 |
| LMArena Korean | — | 1368 |
| LMArena Spanish | — | 1405 |
Instruction Following GPT-5.4 mini leads
GLM-4.6V: 71.4 (#151), GPT-5.4 mini: 74.1 (#102)
| Benchmark | GLM-4.6V | GPT-5.4 mini |
|---|---|---|
| LMArena Instruction Following | 1352 | 1405 |
Long Context GPT-5.4 mini leads
GLM-4.6V: 41.3 (#143), GPT-5.4 mini: 43.0 (#112)
| Benchmark | GLM-4.6V | GPT-5.4 mini |
|---|---|---|
| LMArena Longer Query | 1358 | 1407 |
Writing & Preference GPT-5.4 mini leads
GLM-4.6V: 56.6 (#137), GPT-5.4 mini: 64.0 (#58)
| Benchmark | GLM-4.6V | GPT-5.4 mini |
|---|---|---|
| LMArena Text | 1377 | 1412 |
| LMArena Creative Writing | 1347 | 1370 |
| LMArena Multi-Turn | 1360 | 1429 |
| EQ-Bench Creative Writing | — | 1665 |
Frequently asked questions
Is GLM-4.6V better than GPT-5.4 mini?
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 41.3 on the Noometry Index. GLM-4.6V costs 3.8× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Which is cheaper, GLM-4.6V or GPT-5.4 mini?
GLM-4.6V is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; GPT-5.4 mini lists at $0.75 and $4.50.
Is GLM-4.6V or GPT-5.4 mini better for coding?
GPT-5.4 mini scores higher on coding benchmarks: 45.2 versus 40.9 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 mini does, with 400K tokens against 128K.
How many benchmarks do GLM-4.6V and GPT-5.4 mini share?
12 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and GPT-5.4 mini has 46.