Model comparison
DeepSeek Coder 1.3B vs GLM-4.5V
GLM-4.5V has enough public results to be ranked (#158); DeepSeek Coder 1.3B does not yet, so treat this comparison as directional.
Last verified . 0 shared benchmarks.
DeepSeekSummary
- The widest gap is in coding, where GLM-4.5V leads 39.5 to 31.2.
Side by side
| DeepSeek Coder 1.3B | GLM-4.5V | |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 35.0 | 39.8 |
| Released | 2023-11-02 | 2025-08-11 |
| Weights | Open | Open |
| Context window | — | 64K |
| Max output | — | 16K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $1.80 |
| Results tracked | 9 | 15 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GLM-4.5V leads
DeepSeek Coder 1.3B: 31.2 (#287), GLM-4.5V: 39.5 (#155)
| Benchmark | DeepSeek Coder 1.3B | GLM-4.5V |
|---|---|---|
| BigCodeBench Instruct | 22.8% | — |
| LMArena Coding | — | 1347 |
| BigCodeBench Complete | 29.6% | — |
| HumanEval+ | 60.4% | — |
| MBPP+ | 54.8% | — |
Reasoning Not comparable
DeepSeek Coder 1.3B: —, GLM-4.5V: 27.4 (#119)
| Benchmark | DeepSeek Coder 1.3B | GLM-4.5V |
|---|---|---|
| Kagi LLM Benchmark | — | 59.8% |
| LMArena Hard Prompts | — | 1334 |
| Epoch Capabilities Index | 63.6 | — |
| WinoGrande | 53.3% | — |
Math Not comparable
DeepSeek Coder 1.3B: —, GLM-4.5V: 37.4 (#159)
| Benchmark | DeepSeek Coder 1.3B | GLM-4.5V |
|---|---|---|
| LMArena Math | — | 1354 |
| GSM8K | 4.4% | — |
Knowledge Not comparable
DeepSeek Coder 1.3B: —, GLM-4.5V: 37.5 (#156)
| Benchmark | DeepSeek Coder 1.3B | GLM-4.5V |
|---|---|---|
| LMArena Expert | — | 1353 |
| ARC (AI2) Challenge | 25.4% | — |
| MMLU | 25.8% | — |
Multimodal Not comparable
DeepSeek Coder 1.3B: —, GLM-4.5V: 34.3 (#92)
| Benchmark | DeepSeek Coder 1.3B | GLM-4.5V |
|---|---|---|
| LMArena Vision | — | 1154 |
Multilingual Not comparable
DeepSeek Coder 1.3B: —, GLM-4.5V: 44.6 (#177)
| Benchmark | DeepSeek Coder 1.3B | GLM-4.5V |
|---|---|---|
| LMArena Non-English | — | 1303 |
| LMArena Chinese | — | 1337 |
| LMArena Russian | — | 1298 |
| LMArena Spanish | — | 1336 |
Instruction Following Not comparable
DeepSeek Coder 1.3B: —, GLM-4.5V: 69.2 (#175)
| Benchmark | DeepSeek Coder 1.3B | GLM-4.5V |
|---|---|---|
| LMArena Instruction Following | — | 1311 |
Long Context Not comparable
DeepSeek Coder 1.3B: —, GLM-4.5V: 39.6 (#171)
| Benchmark | DeepSeek Coder 1.3B | GLM-4.5V |
|---|---|---|
| LMArena Longer Query | — | 1304 |
Writing & Preference Not comparable
DeepSeek Coder 1.3B: —, GLM-4.5V: 52.5 (#170)
| Benchmark | DeepSeek Coder 1.3B | GLM-4.5V |
|---|---|---|
| LMArena Text | — | 1333 |
| LMArena Creative Writing | — | 1295 |
| LMArena Multi-Turn | — | 1332 |
Frequently asked questions
Is DeepSeek Coder 1.3B better than GLM-4.5V?
GLM-4.5V has enough public results to be ranked (#158); DeepSeek Coder 1.3B does not yet, so treat this comparison as directional.
Is DeepSeek Coder 1.3B or GLM-4.5V better for coding?
GLM-4.5V scores higher on coding benchmarks: 39.5 versus 31.2 in the Noometry coding category.
How many benchmarks do DeepSeek Coder 1.3B and GLM-4.5V share?
0 benchmarks have published results for both models. DeepSeek Coder 1.3B has 9 scored results on Noometry and GLM-4.5V has 15.