Model comparison
DeepSeek LLM 67B vs GLM-4.7-Flash
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 24.9 on the Noometry Index.
Last verified . 13 shared benchmarks.
DeepSeekSummary
- They share 13 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and GLM-4.7-Flash in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-4.7-Flash leads 35.5 to 7.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.8% for DeepSeek LLM 67B and 58.3% for GLM-4.7-Flash.
Side by side
| DeepSeek LLM 67B | GLM-4.7-Flash | |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 24.9 | 38.8 |
| Released | 2023-11-29 | 2026-01-19 |
| Weights | Open | Open |
| Context window | — | 200K |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.06 |
| Output $ / M tokens | — | $0.40 |
| Results tracked | 15 | 21 |
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Category by category
Coding GLM-4.7-Flash leads
DeepSeek LLM 67B: 31.9 (#278), GLM-4.7-Flash: 40.6 (#135)
| Benchmark | DeepSeek LLM 67B | GLM-4.7-Flash |
|---|---|---|
| LMArena Coding | 1096 | 1383 |
Reasoning GLM-4.7-Flash leads
DeepSeek LLM 67B: 16.5 (#304), GLM-4.7-Flash: 20.9 (#229)
| Benchmark | DeepSeek LLM 67B | GLM-4.7-Flash |
|---|---|---|
| Chess Puzzles | 0% | 0% |
| LMArena Hard Prompts | 1070 | 1356 |
| Epoch Capabilities Index | 110.5 | — |
Math GLM-4.7-Flash leads
DeepSeek LLM 67B: 8.7 (#324), GLM-4.7-Flash: 36.1 (#173)
| Benchmark | DeepSeek LLM 67B | GLM-4.7-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.8% | 58.3% |
| LMArena Math | 1108 | 1355 |
| MATH Level 5 | 6.4% | — |
Knowledge GLM-4.7-Flash leads
DeepSeek LLM 67B: 7.0 (#313), GLM-4.7-Flash: 35.5 (#184)
| Benchmark | DeepSeek LLM 67B | GLM-4.7-Flash |
|---|---|---|
| GPQA Diamond | 24.6% | 60.5% |
| Vectara Hallucination Rate | — | 9.3% |
| LMArena Expert | — | 1357 |
Multilingual GLM-4.7-Flash leads
DeepSeek LLM 67B: 29.4 (#267), GLM-4.7-Flash: 46.5 (#158)
| Benchmark | DeepSeek LLM 67B | GLM-4.7-Flash |
|---|---|---|
| LMArena Non-English | 1073 | 1330 |
| LMArena Chinese | 1132 | 1403 |
| LMArena French | — | 1332 |
| LMArena German | — | 1337 |
| LMArena Korean | — | 1283 |
| LMArena Russian | — | 1332 |
| LMArena Spanish | — | 1350 |
Instruction Following GLM-4.7-Flash leads
DeepSeek LLM 67B: 55.4 (#277), GLM-4.7-Flash: 70.1 (#167)
| Benchmark | DeepSeek LLM 67B | GLM-4.7-Flash |
|---|---|---|
| LMArena Instruction Following | 1079 | 1327 |
Long Context GLM-4.7-Flash leads
DeepSeek LLM 67B: 33.1 (#265), GLM-4.7-Flash: 40.9 (#148)
| Benchmark | DeepSeek LLM 67B | GLM-4.7-Flash |
|---|---|---|
| LMArena Longer Query | 1092 | 1345 |
Writing & Preference GLM-4.7-Flash leads
DeepSeek LLM 67B: 31.6 (#282), GLM-4.7-Flash: 47.4 (#210)
| Benchmark | DeepSeek LLM 67B | GLM-4.7-Flash |
|---|---|---|
| LMArena Text | 1105 | 1351 |
| LMArena Creative Writing | 1067 | 1297 |
| LMArena Multi-Turn | 1082 | 1342 |
| EQ-Bench Creative Writing | — | 1125 |
Frequently asked questions
Is DeepSeek LLM 67B better than GLM-4.7-Flash?
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 24.9 on the Noometry Index.
Is DeepSeek LLM 67B or GLM-4.7-Flash better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 31.9 in the Noometry coding category.
How many benchmarks do DeepSeek LLM 67B and GLM-4.7-Flash share?
13 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and GLM-4.7-Flash has 21.