Model comparison
DeepSeek-R1 vs Step 3.5 Flash
DeepSeek-R1 and Step 3.5 Flash score almost the same on the Noometry Index (42.3 vs 42.3), so choose on price, context window or the category you care about most.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. DeepSeek-R1 scores higher in 6 categories and Step 3.5 Flash in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-R1 leads 44.5 to 39.6.
- Step 3.5 Flash is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.50 / $2.15 for DeepSeek-R1.
- Step 3.5 Flash accepts more context: 256K tokens versus 164K.
- Step 3.5 Flash has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-R1 | Step 3.5 Flash | |
|---|---|---|
| Provider | DeepSeek | StepFun |
| Noometry Index | 42.3 | 42.3 |
| Released | 2025-01-20 | 2026-01-29 |
| Weights | Proprietary | Open |
| Context window | 164K | 256K |
| Max output | 64K | 256K |
| Input $ / M tokens | $0.50 | $0.10 |
| Output $ / M tokens | $2.15 | $0.30 |
| Results tracked | 52 | 19 |
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Category by category
Coding DeepSeek-R1 leads
DeepSeek-R1: 46.3 (#68), Step 3.5 Flash: 42.4 (#105)
| Benchmark | DeepSeek-R1 | Step 3.5 Flash |
|---|---|---|
| LMArena Coding | 1427 | 1436 |
| 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: 30.7 (#75), Step 3.5 Flash: —
| Benchmark | DeepSeek-R1 | Step 3.5 Flash |
|---|---|---|
| DeepResearch Bench | 35.1% | — |
| BALROG | 34.9% | — |
| METR Time Horizons | 53.8% | — |
Reasoning Step 3.5 Flash leads
DeepSeek-R1: 18.6 (#278), Step 3.5 Flash: 22.2 (#202)
| Benchmark | DeepSeek-R1 | Step 3.5 Flash |
|---|---|---|
| LMArena Hard Prompts | 1416 | 1411 |
| 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% | — |
| LiveBench Reasoning | 83.2% | — |
| LiveBench Data Analysis | 69.8% | — |
| Epoch Capabilities Index | 141.29 | — |
| ForecastBench | 60 | — |
| LiveBench | 71.6% | — |
Math DeepSeek-R1 leads
DeepSeek-R1: 43.8 (#79), Step 3.5 Flash: 42.6 (#84)
| Benchmark | DeepSeek-R1 | Step 3.5 Flash |
|---|---|---|
| LMArena Math | 1400 | 1408 |
| MathArena Final-Answer Competitions | — | 66.8% |
| 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: 44.5 (#87), Step 3.5 Flash: 39.6 (#132)
| Benchmark | DeepSeek-R1 | Step 3.5 Flash |
|---|---|---|
| LMArena Expert | 1394 | 1421 |
| GPQA Diamond | 76.3% | — |
| MMLU-Pro | 79.3% | — |
| Confabulations | 12.7% | — |
| Vectara Hallucination Rate | 11.3% | — |
| GPQA (HELM) | 66.6% | — |
Multilingual DeepSeek-R1 leads
DeepSeek-R1: 52.4 (#85), Step 3.5 Flash: 50.5 (#119)
| Benchmark | DeepSeek-R1 | Step 3.5 Flash |
|---|---|---|
| LMArena Non-English | 1412 | 1385 |
| LMArena Chinese | 1442 | 1447 |
| LMArena French | 1417 | 1421 |
| LMArena German | 1404 | 1405 |
| LMArena Japanese | 1391 | 1354 |
| LMArena Korean | 1360 | 1352 |
| LMArena Russian | 1423 | 1385 |
| LMArena Spanish | 1411 | 1419 |
Instruction Following Step 3.5 Flash leads
DeepSeek-R1: 72.0 (#143), Step 3.5 Flash: 73.1 (#124)
| Benchmark | DeepSeek-R1 | Step 3.5 Flash |
|---|---|---|
| LMArena Instruction Following | 1382 | 1385 |
| LiveBench Instruction Following | 80.5% | — |
| IFEval | 78.4% | — |
Long Context DeepSeek-R1 leads
DeepSeek-R1: 45.4 (#36), Step 3.5 Flash: 42.8 (#117)
| Benchmark | DeepSeek-R1 | Step 3.5 Flash |
|---|---|---|
| LMArena Longer Query | 1391 | 1402 |
| Fiction.LiveBench | 75% | — |
Writing & Preference DeepSeek-R1 leads
DeepSeek-R1: 61.4 (#88), Step 3.5 Flash: 58.8 (#113)
| Benchmark | DeepSeek-R1 | Step 3.5 Flash |
|---|---|---|
| LMArena Text | 1428 | 1403 |
| LMArena Creative Writing | 1405 | 1357 |
| LMArena Multi-Turn | 1405 | 1405 |
| 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 Step 3.5 Flash?
DeepSeek-R1 and Step 3.5 Flash score almost the same on the Noometry Index (42.3 vs 42.3), so choose on price, context window or the category you care about most.
Which is cheaper, DeepSeek-R1 or Step 3.5 Flash?
Step 3.5 Flash is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; DeepSeek-R1 lists at $0.50 and $2.15.
Is DeepSeek-R1 or Step 3.5 Flash better for coding?
DeepSeek-R1 scores higher on coding benchmarks: 46.3 versus 42.4 in the Noometry coding category.
Which has the bigger context window?
Step 3.5 Flash does, with 256K tokens against 164K.
How many benchmarks do DeepSeek-R1 and Step 3.5 Flash share?
17 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Step 3.5 Flash has 19.