Model comparison
DeepSeek-V3.1-Terminus vs GPT-5.2 Pro
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 43.1 on the Noometry Index. DeepSeek-V3.1-Terminus costs 128× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
DeepSeekSummary
- The widest gap is in math, where GPT-5.2 Pro leads 65.3 to 38.5.
- DeepSeek-V3.1-Terminus is cheaper at $0.27 / $1 per million input/output tokens, against $21 / $168 for GPT-5.2 Pro.
- GPT-5.2 Pro accepts more context: 400K tokens versus 164K.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1-Terminus | GPT-5.2 Pro | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 43.1 | 52.3 |
| Released | 2025-09-22 | 2025-12-11 |
| Weights | Open | Proprietary |
| Context window | 164K | 400K |
| Max output | 147K | 128K |
| Input $ / M tokens | $0.27 | $21 |
| Output $ / M tokens | $1 | $168 |
| Results tracked | 16 | 8 |
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Category by category
Coding Not comparable
DeepSeek-V3.1-Terminus: 42.0 (#113), GPT-5.2 Pro: —
| Benchmark | DeepSeek-V3.1-Terminus | GPT-5.2 Pro |
|---|---|---|
| SciCode | 40.6% | — |
| LMArena Coding | 1426 | — |
| ALE-Bench | 745.17 | — |
Reasoning GPT-5.2 Pro leads
DeepSeek-V3.1-Terminus: 26.4 (#133), GPT-5.2 Pro: 51.5 (#33)
| Benchmark | DeepSeek-V3.1-Terminus | GPT-5.2 Pro |
|---|---|---|
| ARC-AGI-2 | — | 54.2% |
| SimpleBench | — | 57.4% |
| Kagi LLM Benchmark | 57.4% | — |
| NYT Connections (extended) | — | 79.3% |
| ARC-AGI-1 | — | 90.5% |
| CritPt | 1.7% | — |
| LMArena Hard Prompts | 1426 | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
| Epoch Capabilities Index | — | 155.4 |
Math GPT-5.2 Pro leads
DeepSeek-V3.1-Terminus: 38.5 (#137), GPT-5.2 Pro: 65.3 (#29)
| Benchmark | DeepSeek-V3.1-Terminus | GPT-5.2 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 74% |
| FrontierMath Tier 4 | — | 46% |
| LMArena Math | 1402 | — |
| FrontierMath Tier 4 (v1) | — | 31.3% |
Multilingual Not comparable
DeepSeek-V3.1-Terminus: 52.1 (#92), GPT-5.2 Pro: —
| Benchmark | DeepSeek-V3.1-Terminus | GPT-5.2 Pro |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1436 | — |
Instruction Following Not comparable
DeepSeek-V3.1-Terminus: 74.0 (#106), GPT-5.2 Pro: —
| Benchmark | DeepSeek-V3.1-Terminus | GPT-5.2 Pro |
|---|---|---|
| LMArena Instruction Following | 1404 | — |
Long Context Not comparable
DeepSeek-V3.1-Terminus: 43.4 (#97), GPT-5.2 Pro: —
| Benchmark | DeepSeek-V3.1-Terminus | GPT-5.2 Pro |
|---|---|---|
| LMArena Longer Query | 1421 | — |
Writing & Preference Not comparable
DeepSeek-V3.1-Terminus: 61.0 (#92), GPT-5.2 Pro: —
| Benchmark | DeepSeek-V3.1-Terminus | GPT-5.2 Pro |
|---|---|---|
| LMArena Text | 1419 | — |
| LMArena Creative Writing | 1403 | — |
| LMArena Multi-Turn | 1411 | — |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than GPT-5.2 Pro?
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 43.1 on the Noometry Index. DeepSeek-V3.1-Terminus costs 128× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3.1-Terminus or GPT-5.2 Pro?
DeepSeek-V3.1-Terminus is cheaper. It lists at $0.27 per million input tokens and $1 per million output tokens; GPT-5.2 Pro lists at $21 and $168.
Which has the bigger context window?
GPT-5.2 Pro does, with 400K tokens against 164K.
How many benchmarks do DeepSeek-V3.1-Terminus and GPT-5.2 Pro share?
0 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and GPT-5.2 Pro has 8.