Model comparison
DeepSeek-R1 vs Seed 2.0 Pro
DeepSeek-R1 and Seed 2.0 Pro score almost the same on the Noometry Index (42.0 vs 42.5), so choose on price, context window or the category you care about most.
Last verified . 17 shared benchmarks.
DeepSeek
ByteDance SeedSummary
- They share 17 benchmarks with published results for both. DeepSeek-R1 scores higher in 4 categories and Seed 2.0 Pro in 4 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek-R1 leads 42.0 to 36.5.
- DeepSeek-R1 is cheaper at $0.50 / $2.15 per million input/output tokens, against $0.50 / $3 for Seed 2.0 Pro.
- Seed 2.0 Pro accepts more context: 256K tokens versus 164K.
Side by side
| DeepSeek-R1 | Seed 2.0 Pro | |
|---|---|---|
| Provider | DeepSeek | ByteDance Seed |
| Noometry Index | 42.0 | 42.5 |
| Released | 2025-01-20 | 2026-02-14 |
| Weights | Proprietary | Proprietary |
| Context window | 164K | 256K |
| Max output | 64K | 128K |
| Input $ / M tokens | $0.50 | $0.50 |
| Output $ / M tokens | $2.15 | $3 |
| Results tracked | 52 | 20 |
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Category by category
Coding DeepSeek-R1 leads
DeepSeek-R1: 45.9 (#63), Seed 2.0 Pro: 42.9 (#84)
| Benchmark | DeepSeek-R1 | Seed 2.0 Pro |
|---|---|---|
| LMArena Coding | 1427 | 1472 |
| Aider Polyglot | 71.4% | — |
| SciCode | 35.7% | — |
| WeirdML | 41.6% | — |
| LiveBench Coding | 66.7% | — |
| ALE-Bench | 804.12 | — |
| AlgoTune | 1.7 | — |
Agentic & Tool Use Not comparable
DeepSeek-R1: 30.4 (#68), Seed 2.0 Pro: —
| Benchmark | DeepSeek-R1 | Seed 2.0 Pro |
|---|---|---|
| DeepResearch Bench | 35.1% | — |
| BALROG | 34.9% | — |
| METR Time Horizons | 53.8% | — |
Reasoning Seed 2.0 Pro leads
DeepSeek-R1: 18.7 (#253), Seed 2.0 Pro: 23.1 (#167)
| Benchmark | DeepSeek-R1 | Seed 2.0 Pro |
|---|---|---|
| LMArena Hard Prompts | 1415 | 1453 |
| ARC-AGI-2 | 1.3% | — |
| SimpleBench | 40.8% | — |
| Kagi LLM Benchmark | 69.4% | — |
| NYT Connections (extended) | — | 28.4% |
| ARC-AGI-1 | 21.2% | — |
| CritPt | 1.1% | — |
| Thematic Generalization | — | 57.1% |
| LiveBench Reasoning | 83.2% | — |
| LiveBench Data Analysis | 69.8% | — |
| Epoch Capabilities Index | 141.3 | — |
| ForecastBench | 60 | — |
| LiveBench | 71.6% | — |
Math DeepSeek-R1 leads
DeepSeek-R1: 42.0 (#70), Seed 2.0 Pro: 36.5 (#110)
| Benchmark | DeepSeek-R1 | Seed 2.0 Pro |
|---|---|---|
| LMArena Math | 1401 | 1440 |
| OTIS Mock AIME 2024-2025 | 66.4% | — |
| Omni-MATH | 42.4% | — |
| LiveBench Math | 80.7% | — |
| MATH Level 5 | 96.6% | — |
Knowledge DeepSeek-R1 leads
DeepSeek-R1: 44.3 (#81), Seed 2.0 Pro: 39.6 (#119)
| Benchmark | DeepSeek-R1 | Seed 2.0 Pro |
|---|---|---|
| LMArena Expert | 1394 | 1440 |
| GPQA Diamond | 76.3% | — |
| MMLU-Pro | 79.3% | — |
| Confabulations | 12.7% | — |
| Vectara Hallucination Rate | 11.3% | — |
| GPQA (HELM) | 66.6% | — |
Multimodal Not comparable
DeepSeek-R1: —, Seed 2.0 Pro: 40.8 (#34)
| Benchmark | DeepSeek-R1 | Seed 2.0 Pro |
|---|---|---|
| LMArena Vision | — | 1275 |
Multilingual Seed 2.0 Pro leads
DeepSeek-R1: 52.6 (#80), Seed 2.0 Pro: 54.8 (#37)
| Benchmark | DeepSeek-R1 | Seed 2.0 Pro |
|---|---|---|
| LMArena Non-English | 1412 | 1442 |
| LMArena Chinese | 1443 | 1490 |
| LMArena French | 1415 | 1470 |
| LMArena German | 1405 | 1443 |
| LMArena Japanese | 1394 | 1408 |
| LMArena Korean | 1359 | 1412 |
| LMArena Russian | 1423 | 1450 |
| LMArena Spanish | 1410 | 1460 |
Instruction Following Seed 2.0 Pro leads
DeepSeek-R1: 72.2 (#138), Seed 2.0 Pro: 74.7 (#86)
| Benchmark | DeepSeek-R1 | Seed 2.0 Pro |
|---|---|---|
| LMArena Instruction Following | 1382 | 1414 |
| LiveBench Instruction Following | 80.5% | — |
| IFEval | 78.4% | — |
Long Context DeepSeek-R1 leads
DeepSeek-R1: 45.4 (#36), Seed 2.0 Pro: 43.6 (#85)
| Benchmark | DeepSeek-R1 | Seed 2.0 Pro |
|---|---|---|
| LMArena Longer Query | 1391 | 1428 |
| Fiction.LiveBench | 75% | — |
Writing & Preference Seed 2.0 Pro leads
DeepSeek-R1: 61.5 (#84), Seed 2.0 Pro: 63.0 (#66)
| Benchmark | DeepSeek-R1 | Seed 2.0 Pro |
|---|---|---|
| LMArena Text | 1428 | 1448 |
| LMArena Creative Writing | 1406 | 1406 |
| LMArena Multi-Turn | 1404 | 1441 |
| Short-Story Creative Writing | 83% | — |
| EQ-Bench Creative Writing | 1500 | — |
| WildBench | 82.8% | — |
| LiveBench Language | 48.5% | — |
Frequently asked questions
Is DeepSeek-R1 better than Seed 2.0 Pro?
DeepSeek-R1 and Seed 2.0 Pro score almost the same on the Noometry Index (42.0 vs 42.5), so choose on price, context window or the category you care about most.
Which is cheaper, DeepSeek-R1 or Seed 2.0 Pro?
DeepSeek-R1 is cheaper. It lists at $0.50 per million input tokens and $2.15 per million output tokens; Seed 2.0 Pro lists at $0.50 and $3.
Is DeepSeek-R1 or Seed 2.0 Pro better for coding?
DeepSeek-R1 scores higher on coding benchmarks: 45.9 versus 42.9 in the Noometry coding category.
Which has the bigger context window?
Seed 2.0 Pro does, with 256K tokens against 164K.
How many benchmarks do DeepSeek-R1 and Seed 2.0 Pro share?
17 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Seed 2.0 Pro has 20.