Model comparison
DeepSeek-V3.1-Terminus vs Mercury 2.5
DeepSeek-V3.1-Terminus has enough public results to be ranked (#96); Mercury 2.5 does not yet, so treat this comparison as directional.
Last verified . 1 shared benchmarks.
DeepSeekSummary
- They share 1 benchmark with published results for both. DeepSeek-V3.1-Terminus scores higher in 1 category and Mercury 2.5 in 0 categories; one gap is clear of the uncertainty.
- The widest gap is in math, where DeepSeek-V3.1-Terminus leads 35.7 to 22.4.
- Mercury 2.5 is cheaper at $0.04 / $0.15 per million input/output tokens, against $0.30 / $1 for DeepSeek-V3.1-Terminus.
- Mercury 2.5 accepts more context: 260K tokens versus 164K.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1-Terminus | Mercury 2.5 | |
|---|---|---|
| Provider | DeepSeek | Inception |
| Noometry Index | 42.6 | 30.2 |
| Released | 2025-09-22 | 2026-09-08 |
| Weights | Open | Proprietary |
| Context window | 164K | 260K |
| Max output | 66K | 66K |
| Input $ / M tokens | $0.30 | $0.04 |
| Output $ / M tokens | $1 | $0.15 |
| Results tracked | 16 | 2 |
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Category by category
Coding Not comparable
DeepSeek-V3.1-Terminus: 41.5 (#114), Mercury 2.5: —
| Benchmark | DeepSeek-V3.1-Terminus | Mercury 2.5 |
|---|---|---|
| ALE-Bench | 745.17 | 301.65 |
| SciCode | 40.6% | — |
| LMArena Coding | 1426 | — |
Reasoning Not comparable
DeepSeek-V3.1-Terminus: 25.7 (#126), Mercury 2.5: —
| Benchmark | DeepSeek-V3.1-Terminus | Mercury 2.5 |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| LMArena Hard Prompts | 1427 | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 35.7 (#138), Mercury 2.5: 22.4
| Benchmark | DeepSeek-V3.1-Terminus | Mercury 2.5 |
|---|---|---|
| ProofBench | — | 3% |
| LMArena Math | 1402 | — |
Multilingual Not comparable
DeepSeek-V3.1-Terminus: 52.3 (#87), Mercury 2.5: —
| Benchmark | DeepSeek-V3.1-Terminus | Mercury 2.5 |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1434 | — |
Instruction Following Not comparable
DeepSeek-V3.1-Terminus: 74.4 (#96), Mercury 2.5: —
| Benchmark | DeepSeek-V3.1-Terminus | Mercury 2.5 |
|---|---|---|
| LMArena Instruction Following | 1406 | — |
Long Context Not comparable
DeepSeek-V3.1-Terminus: 43.5 (#88), Mercury 2.5: —
| Benchmark | DeepSeek-V3.1-Terminus | Mercury 2.5 |
|---|---|---|
| LMArena Longer Query | 1426 | — |
Writing & Preference Not comparable
DeepSeek-V3.1-Terminus: 61.3 (#87), Mercury 2.5: —
| Benchmark | DeepSeek-V3.1-Terminus | Mercury 2.5 |
|---|---|---|
| LMArena Text | 1420 | — |
| LMArena Creative Writing | 1404 | — |
| LMArena Multi-Turn | 1411 | — |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Mercury 2.5?
DeepSeek-V3.1-Terminus has enough public results to be ranked (#96); Mercury 2.5 does not yet, so treat this comparison as directional.
Which is cheaper, DeepSeek-V3.1-Terminus or Mercury 2.5?
Mercury 2.5 is cheaper. It lists at $0.04 per million input tokens and $0.15 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.30 and $1.
Which has the bigger context window?
Mercury 2.5 does, with 260K tokens against 164K.
How many benchmarks do DeepSeek-V3.1-Terminus and Mercury 2.5 share?
1 benchmark has published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Mercury 2.5 has 2.