Model comparison
DeepSeek-V3 vs GLM-4.5-Air
DeepSeek-V3 and GLM-4.5-Air score almost the same on the Noometry Index (39.5 vs 38.9), so choose on price, context window or the category you care about most.
Last verified . 25 shared benchmarks.
DeepSeekSummary
- They share 25 benchmarks with published results for both. DeepSeek-V3 scores higher in 4 categories and GLM-4.5-Air in 4 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where DeepSeek-V3 leads 42.3 to 33.3.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 52.3% for DeepSeek-V3 and 43% for GLM-4.5-Air.
- Both cost about the same: $0.24 input and $0.90 output per million tokens.
- DeepSeek-V3 accepts more context: 164K tokens versus 131K.
Side by side
| DeepSeek-V3 | GLM-4.5-Air | |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 39.5 | 38.9 |
| Released | 2024-12-26 | 2025-07-20 |
| Weights | Open | Open |
| Context window | 164K | 131K |
| Max output | 164K | 98K |
| Input $ / M tokens | $0.24 | $0.20 |
| Output $ / M tokens | $0.90 | $1.10 |
| Results tracked | 60 | 27 |
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Category by category
Coding DeepSeek-V3 leads
DeepSeek-V3: 42.3 (#106), GLM-4.5-Air: 33.3 (#259)
| Benchmark | DeepSeek-V3 | GLM-4.5-Air |
|---|---|---|
| LMArena Coding | 1368 | 1397 |
| Aider Polyglot | 55.1% | — |
| SciCode | 35.8% | — |
| GSO | — | 2.9% |
| WeirdML | 36.1% | — |
| BigCodeBench Instruct | 50% | — |
| LiveBench Coding | 70.9% | — |
| BigCodeBench Complete | 62.2% | — |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73% | — |
Agentic & Tool Use Not comparable
DeepSeek-V3: —, GLM-4.5-Air: —
| Benchmark | DeepSeek-V3 | GLM-4.5-Air |
|---|---|---|
| METR Time Horizons | 49.6% | — |
Reasoning GLM-4.5-Air leads
DeepSeek-V3: 20.5 (#236), GLM-4.5-Air: 24.1 (#166)
| Benchmark | DeepSeek-V3 | GLM-4.5-Air |
|---|---|---|
| Kagi LLM Benchmark | 52.3% | 43% |
| LMArena Hard Prompts | 1365 | 1379 |
| ForecastBench | 59.1 | 59.2 |
| SimpleBench | 27.2% | — |
| CritPt | 0% | — |
| LiveBench Reasoning | 65.8% | — |
| DTBench | 64.8% | — |
| LiveBench Data Analysis | 60.9% | — |
| LMCA | 15.5% | — |
| BIG-Bench Hard | 87.5% | — |
| Epoch Capabilities Index | 135.94 | — |
| HellaSwag | 88.9% | — |
| LiveBench | 66.9% | — |
| PIQA | 84.7% | — |
| WinoGrande | 85.2% | — |
Math GLM-4.5-Air leads
DeepSeek-V3: 32.1 (#219), GLM-4.5-Air: 36.2 (#170)
| Benchmark | DeepSeek-V3 | GLM-4.5-Air |
|---|---|---|
| Omni-MATH | 40.3% | 39.1% |
| LMArena Math | 1373 | 1396 |
| OTIS Mock AIME 2024-2025 | 37.8% | — |
| LiveBench Math | 73.5% | — |
| MATH Level 5 | 75.5% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |
Knowledge DeepSeek-V3 leads
DeepSeek-V3: 37.5 (#155), GLM-4.5-Air: 35.0 (#191)
| Benchmark | DeepSeek-V3 | GLM-4.5-Air |
|---|---|---|
| MMLU-Pro | 72.3% | 76.2% |
| Vectara Hallucination Rate | 6.1% | 9.3% |
| GPQA (HELM) | 53.8% | 59.4% |
| LMArena Expert | 1351 | 1370 |
| GPQA Diamond | 67.6% | — |
| Humanity's Last Exam | — | 8.1% |
| Confabulations | 26.1% | — |
| ARC (AI2) Challenge | 95.3% | — |
| MMLU | 87.2% | — |
| TriviaQA | 82.9% | — |
Multilingual Too close to call
DeepSeek-V3: 48.5 (#143), GLM-4.5-Air: 49.1 (#135)
| Benchmark | DeepSeek-V3 | GLM-4.5-Air |
|---|---|---|
| LMArena Non-English | 1358 | 1366 |
| LMArena Chinese | 1391 | 1426 |
| LMArena French | 1385 | 1399 |
| LMArena German | 1374 | 1377 |
| LMArena Japanese | 1333 | 1348 |
| LMArena Korean | 1319 | 1308 |
| LMArena Russian | 1373 | 1373 |
| LMArena Spanish | 1358 | 1386 |
Instruction Following DeepSeek-V3 leads
DeepSeek-V3: 72.8 (#130), GLM-4.5-Air: 69.6 (#171)
| Benchmark | DeepSeek-V3 | GLM-4.5-Air |
|---|---|---|
| IFEval | 83.2% | 81.2% |
| LMArena Instruction Following | 1345 | 1354 |
| LiveBench Instruction Following | 81.5% | — |
Long Context GLM-4.5-Air leads
DeepSeek-V3: 34.0 (#253), GLM-4.5-Air: 41.6 (#135)
| Benchmark | DeepSeek-V3 | GLM-4.5-Air |
|---|---|---|
| LMArena Longer Query | 1352 | 1366 |
| Fiction.LiveBench | 50% | — |
Writing & Preference DeepSeek-V3 leads
DeepSeek-V3: 57.4 (#130), GLM-4.5-Air: 55.9 (#139)
| Benchmark | DeepSeek-V3 | GLM-4.5-Air |
|---|---|---|
| LMArena Text | 1375 | 1384 |
| LMArena Creative Writing | 1364 | 1343 |
| WildBench | 83% | 78.9% |
| LMArena Multi-Turn | 1389 | 1371 |
| Short-Story Creative Writing | 77% | — |
| EQ-Bench Creative Writing | 1472 | — |
| LiveBench Language | 49.1% | — |
Frequently asked questions
Is DeepSeek-V3 better than GLM-4.5-Air?
DeepSeek-V3 and GLM-4.5-Air score almost the same on the Noometry Index (39.5 vs 38.9), so choose on price, context window or the category you care about most.
Which is cheaper, DeepSeek-V3 or GLM-4.5-Air?
DeepSeek-V3 is cheaper. It lists at $0.24 per million input tokens and $0.90 per million output tokens; GLM-4.5-Air lists at $0.20 and $1.10.
Is DeepSeek-V3 or GLM-4.5-Air better for coding?
DeepSeek-V3 scores higher on coding benchmarks: 42.3 versus 33.3 in the Noometry coding category.
Which has the bigger context window?
DeepSeek-V3 does, with 164K tokens against 131K.
How many benchmarks do DeepSeek-V3 and GLM-4.5-Air share?
25 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and GLM-4.5-Air has 27.