Model comparison
DeepSeek LLM 67B vs GLM-4.5V
GLM-4.5V is the stronger model overall, scoring 39.8 to 24.9 on the Noometry Index.
Last verified . 10 shared benchmarks.
DeepSeekSummary
- They share 10 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and GLM-4.5V in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-4.5V leads 37.5 to 7.0.
Side by side
| DeepSeek LLM 67B | GLM-4.5V | |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 24.9 | 39.8 |
| Released | 2023-11-29 | 2025-08-11 |
| Weights | Open | Open |
| Context window | — | 64K |
| Max output | — | 16K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $1.80 |
| Results tracked | 15 | 15 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GLM-4.5V leads
DeepSeek LLM 67B: 31.9 (#278), GLM-4.5V: 39.5 (#155)
| Benchmark | DeepSeek LLM 67B | GLM-4.5V |
|---|---|---|
| LMArena Coding | 1096 | 1347 |
Reasoning GLM-4.5V leads
DeepSeek LLM 67B: 16.5 (#304), GLM-4.5V: 27.4 (#119)
| Benchmark | DeepSeek LLM 67B | GLM-4.5V |
|---|---|---|
| LMArena Hard Prompts | 1070 | 1334 |
| Kagi LLM Benchmark | — | 59.8% |
| Chess Puzzles | 0% | — |
| Epoch Capabilities Index | 110.5 | — |
Math GLM-4.5V leads
DeepSeek LLM 67B: 8.7 (#324), GLM-4.5V: 37.4 (#159)
| Benchmark | DeepSeek LLM 67B | GLM-4.5V |
|---|---|---|
| LMArena Math | 1108 | 1354 |
| OTIS Mock AIME 2024-2025 | 0.8% | — |
| MATH Level 5 | 6.4% | — |
Knowledge GLM-4.5V leads
DeepSeek LLM 67B: 7.0 (#313), GLM-4.5V: 37.5 (#156)
| Benchmark | DeepSeek LLM 67B | GLM-4.5V |
|---|---|---|
| GPQA Diamond | 24.6% | — |
| LMArena Expert | — | 1353 |
Multimodal Not comparable
DeepSeek LLM 67B: —, GLM-4.5V: 34.3 (#92)
| Benchmark | DeepSeek LLM 67B | GLM-4.5V |
|---|---|---|
| LMArena Vision | — | 1154 |
Multilingual GLM-4.5V leads
DeepSeek LLM 67B: 29.4 (#267), GLM-4.5V: 44.6 (#177)
| Benchmark | DeepSeek LLM 67B | GLM-4.5V |
|---|---|---|
| LMArena Non-English | 1073 | 1303 |
| LMArena Chinese | 1132 | 1337 |
| LMArena Russian | — | 1298 |
| LMArena Spanish | — | 1336 |
Instruction Following GLM-4.5V leads
DeepSeek LLM 67B: 55.4 (#277), GLM-4.5V: 69.2 (#175)
| Benchmark | DeepSeek LLM 67B | GLM-4.5V |
|---|---|---|
| LMArena Instruction Following | 1079 | 1311 |
Long Context GLM-4.5V leads
DeepSeek LLM 67B: 33.1 (#265), GLM-4.5V: 39.6 (#171)
| Benchmark | DeepSeek LLM 67B | GLM-4.5V |
|---|---|---|
| LMArena Longer Query | 1092 | 1304 |
Writing & Preference GLM-4.5V leads
DeepSeek LLM 67B: 31.6 (#282), GLM-4.5V: 52.5 (#170)
| Benchmark | DeepSeek LLM 67B | GLM-4.5V |
|---|---|---|
| LMArena Text | 1105 | 1333 |
| LMArena Creative Writing | 1067 | 1295 |
| LMArena Multi-Turn | 1082 | 1332 |
Frequently asked questions
Is DeepSeek LLM 67B better than GLM-4.5V?
GLM-4.5V is the stronger model overall, scoring 39.8 to 24.9 on the Noometry Index.
Is DeepSeek LLM 67B or GLM-4.5V better for coding?
GLM-4.5V scores higher on coding benchmarks: 39.5 versus 31.9 in the Noometry coding category.
How many benchmarks do DeepSeek LLM 67B and GLM-4.5V share?
10 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and GLM-4.5V has 15.