Model comparison
DeepSeek-V3.1-Terminus vs phi-3-medium 14B
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 29.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
MicrosoftSummary
- The widest gap is in math, where DeepSeek-V3.1-Terminus leads 38.5 to 27.3.
Side by side
| DeepSeek-V3.1-Terminus | phi-3-medium 14B | |
|---|---|---|
| Provider | DeepSeek | Microsoft |
| Noometry Index | 43.1 | 29.7 |
| Released | 2025-09-22 | 2024-04-23 |
| Weights | Open | Open |
| Context window | 164K | — |
| Max output | 147K | — |
| Input $ / M tokens | $0.27 | — |
| Output $ / M tokens | $1 | — |
| Results tracked | 16 | 13 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 42.0 (#113), phi-3-medium 14B: 36.8 (#201)
| Benchmark | DeepSeek-V3.1-Terminus | phi-3-medium 14B |
|---|---|---|
| SciCode | 40.6% | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1426 | — |
| BigCodeBench Complete | — | 48.7% |
| ALE-Bench | 745.17 | — |
Reasoning Not comparable
DeepSeek-V3.1-Terminus: 26.4 (#133), phi-3-medium 14B: —
| Benchmark | DeepSeek-V3.1-Terminus | phi-3-medium 14B |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| LMArena Hard Prompts | 1426 | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
| Adversarial NLI | — | 55.8% |
| BIG-Bench Hard | — | 81.4% |
| Epoch Capabilities Index | — | 121.23 |
| HellaSwag | — | 82.4% |
| WinoGrande | — | 81.5% |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 38.5 (#137), phi-3-medium 14B: 27.3 (#250)
| Benchmark | DeepSeek-V3.1-Terminus | phi-3-medium 14B |
|---|---|---|
| LMArena Math | 1402 | — |
| MATH Level 5 | — | 17.6% |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, phi-3-medium 14B: 9.1 (#306)
| Benchmark | DeepSeek-V3.1-Terminus | phi-3-medium 14B |
|---|---|---|
| GPQA Diamond | — | 27.6% |
| ARC (AI2) Challenge | — | 91.6% |
| MMLU | — | 78% |
| OpenBookQA | — | 87.4% |
| TriviaQA | — | 73.9% |
Multilingual Not comparable
DeepSeek-V3.1-Terminus: 52.1 (#92), phi-3-medium 14B: —
| Benchmark | DeepSeek-V3.1-Terminus | phi-3-medium 14B |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1436 | — |
Instruction Following Not comparable
DeepSeek-V3.1-Terminus: 74.0 (#106), phi-3-medium 14B: —
| Benchmark | DeepSeek-V3.1-Terminus | phi-3-medium 14B |
|---|---|---|
| LMArena Instruction Following | 1404 | — |
Long Context Not comparable
DeepSeek-V3.1-Terminus: 43.4 (#97), phi-3-medium 14B: —
| Benchmark | DeepSeek-V3.1-Terminus | phi-3-medium 14B |
|---|---|---|
| LMArena Longer Query | 1421 | — |
Writing & Preference Not comparable
DeepSeek-V3.1-Terminus: 61.0 (#92), phi-3-medium 14B: —
| Benchmark | DeepSeek-V3.1-Terminus | phi-3-medium 14B |
|---|---|---|
| LMArena Text | 1419 | — |
| LMArena Creative Writing | 1403 | — |
| LMArena Multi-Turn | 1411 | — |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than phi-3-medium 14B?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 29.7 on the Noometry Index.
Is DeepSeek-V3.1-Terminus or phi-3-medium 14B better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 36.8 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.1-Terminus and phi-3-medium 14B share?
0 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and phi-3-medium 14B has 13.