Model comparison
DeepSeek-V3.1-Terminus vs GLM-4.5V
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 39.2 on the Noometry Index.
Last verified . 11 shared benchmarks.
DeepSeekSummary
- They share 11 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 6 categories and GLM-4.5V in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.3 to 52.7.
- DeepSeek-V3.1-Terminus is cheaper at $0.30 / $1 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
- DeepSeek-V3.1-Terminus accepts more context: 164K tokens versus 64K.
Side by side
| DeepSeek-V3.1-Terminus | GLM-4.5V | |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 42.6 | 39.2 |
| Released | 2025-09-22 | 2025-08-11 |
| Weights | Open | Open |
| Context window | 164K | 64K |
| Max output | 66K | 16K |
| Input $ / M tokens | $0.30 | $0.60 |
| Output $ / M tokens | $1 | $1.80 |
| Results tracked | 16 | 15 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 41.5 (#114), GLM-4.5V: 38.9 (#152)
| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.5V |
|---|---|---|
| LMArena Coding | 1426 | 1347 |
| SciCode | 40.6% | — |
| ALE-Bench | 745.17 | — |
Reasoning Too close to call
DeepSeek-V3.1-Terminus: 25.7 (#126), GLM-4.5V: 26.5 (#118)
| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.5V |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | 59.8% |
| LMArena Hard Prompts | 1427 | 1335 |
| CritPt | 1.7% | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 35.7 (#138), GLM-4.5V: 34.7 (#157)
| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.5V |
|---|---|---|
| LMArena Math | 1402 | 1353 |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, GLM-4.5V: 36.8 (#155)
| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.5V |
|---|---|---|
| LMArena Expert | — | 1353 |
Multimodal Not comparable
DeepSeek-V3.1-Terminus: —, GLM-4.5V: 33.6 (#86)
| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.5V |
|---|---|---|
| LMArena Vision | — | 1154 |
Multilingual DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 52.3 (#87), GLM-4.5V: 44.9 (#172)
| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.5V |
|---|---|---|
| LMArena Non-English | 1407 | 1304 |
| LMArena Russian | 1434 | 1299 |
| LMArena Chinese | — | 1338 |
| LMArena Spanish | — | 1335 |
Instruction Following DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 74.4 (#96), GLM-4.5V: 69.4 (#170)
| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.5V |
|---|---|---|
| LMArena Instruction Following | 1406 | 1311 |
Long Context DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 43.5 (#88), GLM-4.5V: 39.6 (#166)
| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.5V |
|---|---|---|
| LMArena Longer Query | 1426 | 1305 |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.3 (#87), GLM-4.5V: 52.7 (#162)
| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.5V |
|---|---|---|
| LMArena Text | 1420 | 1333 |
| LMArena Creative Writing | 1404 | 1295 |
| LMArena Multi-Turn | 1411 | 1333 |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than GLM-4.5V?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 39.2 on the Noometry Index.
Which is cheaper, DeepSeek-V3.1-Terminus or GLM-4.5V?
DeepSeek-V3.1-Terminus is cheaper. It lists at $0.30 per million input tokens and $1 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.
Is DeepSeek-V3.1-Terminus or GLM-4.5V better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 41.5 versus 38.9 in the Noometry coding category.
Which has the bigger context window?
DeepSeek-V3.1-Terminus does, with 164K tokens against 64K.
How many benchmarks do DeepSeek-V3.1-Terminus and GLM-4.5V share?
11 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and GLM-4.5V has 15.