Model comparison
DeepSeek V4 Flash vs GLM-4.7-Flash
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 1.8× less per token, which makes it the better buy when DeepSeek V4 Flash's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
DeepSeekSummary
- They share 20 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 8 categories and GLM-4.7-Flash in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Flash leads 53.7 to 20.9.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 94.4% for DeepSeek V4 Flash and 58.3% for GLM-4.7-Flash.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.15 / $0.60 for DeepSeek V4 Flash.
- DeepSeek V4 Flash accepts more context: 1M tokens versus 200K.
Side by side
| DeepSeek V4 Flash | GLM-4.7-Flash | |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 53.6 | 38.8 |
| Released | 2026-04-24 | 2026-01-19 |
| Weights | Open | Open |
| Context window | 1M | 200K |
| Max output | 393K | 131K |
| Input $ / M tokens | $0.15 | $0.06 |
| Output $ / M tokens | $0.60 | $0.40 |
| Results tracked | 41 | 21 |
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Category by category
Coding DeepSeek V4 Flash leads
DeepSeek V4 Flash: 47.9 (#59), GLM-4.7-Flash: 40.6 (#135)
| Benchmark | DeepSeek V4 Flash | GLM-4.7-Flash |
|---|---|---|
| LMArena Coding | 1457 | 1383 |
| FrontierCode | 18.8% | — |
| LMArena WebDev | 1582 | — |
| SciCode | 49.9% | — |
| WeirdML | 63% | — |
| ALE-Bench | 1,306 | — |
Reasoning DeepSeek V4 Flash leads
DeepSeek V4 Flash: 53.7 (#30), GLM-4.7-Flash: 20.9 (#229)
| Benchmark | DeepSeek V4 Flash | GLM-4.7-Flash |
|---|---|---|
| Chess Puzzles | 33% | 0% |
| LMArena Hard Prompts | 1444 | 1356 |
| ARC-AGI-2 | 61.4% | — |
| SimpleBench | 61.1% | — |
| Kagi LLM Benchmark | 52.2% | — |
| NYT Connections (extended) | 89.6% | — |
| ARC-AGI-1 | 89% | — |
| CritPt | 16.6% | — |
| Mystery Game Puzzles | 34% | — |
| DTBench | 90.9% | — |
| LMCA | 41.7% | — |
| Epoch Capabilities Index | 154.49 | — |
Math DeepSeek V4 Flash leads
DeepSeek V4 Flash: 60.3 (#37), GLM-4.7-Flash: 36.1 (#173)
| Benchmark | DeepSeek V4 Flash | GLM-4.7-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 94.4% | 58.3% |
| LMArena Math | 1427 | 1355 |
| FrontierMath (Tiers 1-3) | 57.5% | — |
| FrontierMath Tier 4 | 24.4% | — |
| MathArena Final-Answer Competitions | 76.5% | — |
| ProofBench | 56% | — |
Knowledge DeepSeek V4 Flash leads
DeepSeek V4 Flash: 55.4 (#48), GLM-4.7-Flash: 35.5 (#184)
| Benchmark | DeepSeek V4 Flash | GLM-4.7-Flash |
|---|---|---|
| GPQA Diamond | 91% | 60.5% |
| LMArena Expert | 1441 | 1357 |
| SimpleQA Verified | 33.6% | — |
| Vectara Hallucination Rate | — | 9.3% |
Multilingual DeepSeek V4 Flash leads
DeepSeek V4 Flash: 53.0 (#72), GLM-4.7-Flash: 46.5 (#158)
| Benchmark | DeepSeek V4 Flash | GLM-4.7-Flash |
|---|---|---|
| LMArena Non-English | 1420 | 1330 |
| LMArena Chinese | 1468 | 1403 |
| LMArena French | 1439 | 1332 |
| LMArena German | 1418 | 1337 |
| LMArena Korean | 1384 | 1283 |
| LMArena Russian | 1428 | 1332 |
| LMArena Spanish | 1436 | 1350 |
| LMArena Japanese | 1406 | — |
Instruction Following DeepSeek V4 Flash leads
DeepSeek V4 Flash: 74.9 (#81), GLM-4.7-Flash: 70.1 (#167)
| Benchmark | DeepSeek V4 Flash | GLM-4.7-Flash |
|---|---|---|
| LMArena Instruction Following | 1421 | 1327 |
Long Context DeepSeek V4 Flash leads
DeepSeek V4 Flash: 43.8 (#85), GLM-4.7-Flash: 40.9 (#148)
| Benchmark | DeepSeek V4 Flash | GLM-4.7-Flash |
|---|---|---|
| LMArena Longer Query | 1434 | 1345 |
Writing & Preference DeepSeek V4 Flash leads
DeepSeek V4 Flash: 63.8 (#61), GLM-4.7-Flash: 47.4 (#210)
| Benchmark | DeepSeek V4 Flash | GLM-4.7-Flash |
|---|---|---|
| LMArena Text | 1432 | 1351 |
| LMArena Creative Writing | 1403 | 1297 |
| EQ-Bench Creative Writing | 1559 | 1125 |
| LMArena Multi-Turn | 1449 | 1342 |
Frequently asked questions
Is DeepSeek V4 Flash better than GLM-4.7-Flash?
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 1.8× less per token, which makes it the better buy when DeepSeek V4 Flash's lead doesn't matter for your workload.
Which is cheaper, DeepSeek V4 Flash or GLM-4.7-Flash?
GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; DeepSeek V4 Flash lists at $0.15 and $0.60.
Is DeepSeek V4 Flash or GLM-4.7-Flash better for coding?
DeepSeek V4 Flash scores higher on coding benchmarks: 47.9 versus 40.6 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4 Flash does, with 1M tokens against 200K.
How many benchmarks do DeepSeek V4 Flash and GLM-4.7-Flash share?
20 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and GLM-4.7-Flash has 21.