DeepSeek V4.1 Flash vs DeepSeek V4 Pro
DeepSeek V4.1 Flash scores higher on 3 of the 4 benchmarks both models publish. The widest gap is on Humanity's Last Exam, where DeepSeek V4 Pro leads by 5.9 points. Both have open weights; DeepSeek V4.1 Flash is far lighter to host, needing about 381 GB at 4-bit against 1.1 TB for DeepSeek V4 Pro.
Shared benchmarks
Raw published scores; the higher score on each row is highlighted. LMArena Elo is a human-preference vote and is not counted as a win.
- GPQA Diamond90.990.1
Pass@1, max reasoning effortV4-Pro (Preview) Max, pass@1
- Humanity's Last Exam36.842.7
Pass@1, no tools, max effort (text-only subset: 39.1)V4-Pro-0813, no tools
- Humanity's Last Exam (with tools)63.960.0
Pass@1, with tools, max effortV4-Pro-0813, with tools
- Terminal-Bench90.687.9
Terminal-Bench 2.1, Pass@1, max effortTerminal-Bench 2.1, V4-Pro-0813, max effort, DeepSeek Harness
- LMArena Text Elo · not counted14761465
LMArena text overall, 'DeepSeek-V4.1-Flash-20260910 (Max)', ±6, as of 2026-10-27DeepSeek-V4-Pro (High, 20260813), ±7, board dated 2026-10-27
Should you pick DeepSeek V4.1 Flash or DeepSeek V4 Pro?
Pick DeepSeek V4.1 Flash if…
- You care most about Humanity's Last Exam (with tools), Terminal-Bench, where it scores at least 2 points higher.
- People prefer its answers in blind chats: LMArena Elo 1476 against 1465.
- You want the lighter model to host: about 381 GB at 4-bit against 1.1 TB.
- You need fast responses: about 217 tokens per second through APIs, against 94.
- Cost matters: $1.20 per million output tokens against $3.96.
- You want it running in minutes on a dedicated GPU through OpenLLM Buddy, in an uncensored build.
Pick DeepSeek V4 Pro if…
- You care most about Humanity's Last Exam, where it scores at least 2 points higher.
Hardware and cost to run
DeepSeek V4.1 Flash
Even at 4-bit it needs about 381 GB (4× H200 (564 GB)), well beyond a home workstation, so most people run it on rented multi-GPU servers. Full BF16 precision needs about 1.3 TB (Multiple nodes (over 1.1 TB)).
On OpenLLM Buddy: DeepSeek-V4.1-Flash-UNCENSORED-FP8 runs on 4× H200 141GB as an FP8 build, with an OpenAI-compatible API and no per-token fees. Prices start at $280 USD for 11 hours.
Deploy DeepSeek V4.1 FlashDeepSeek V4 Pro
Even at 4-bit it needs about 1.1 TB (8× H200 (1,128 GB)), well beyond a home workstation, so most people run it on rented multi-GPU servers. Full BF16 precision needs about 3.7 TB (Multiple nodes (over 1.1 TB)).
Category profile
Category index uses every test each model reports, not only the shared ones.
Specs side by side
| DeepSeek V4.1 Flash | DeepSeek V4 Pro | |
|---|---|---|
| Lab | DeepSeek | DeepSeek |
| Weights | Open | Open |
| Released | 2026-09-10 | 2026-08-13 |
| Parameters | 552B total, 16B active (MoE) | 1.6T total, 49B active (MoE) |
| Context | 1M | 1M |
| License | MIT | MIT |
| 4-bit memory | 381 GB · 4× H200 (564 GB) | 1.1 TB · 8× H200 (1,128 GB) |
| API price | $0.300 in / $1.20 out per 1M tokens | $1.32 in / $3.96 out per 1M tokens |
| API speed | 217 tok/s | 94 tok/s |
Related comparisons
- DeepSeek V4.1 Flash vs GPT-6 Astra
- DeepSeek V4.1 Flash vs Claude Opus 5.5
- DeepSeek V4.1 Flash vs Gemini 3.8 Flash
DeepSeek V4.1 Flash vs MiMo V2.6 Pro
GLM 5.3 Flash vs DeepSeek V4.1 Flash
Qwen3.8 27B vs DeepSeek V4.1 Flash
Gemma 4 31B vs DeepSeek V4.1 Flash
Kimi K3 vs DeepSeek V4 Pro
GLM 5.3 vs DeepSeek V4 Pro
- DeepSeek V4 Pro vs Claude Fable 5.1
Sources
| Model | Test | Score | Setting | Source |
|---|---|---|---|---|
| DeepSeek V4.1 Flash | GPQA Diamond | 90.9 | Pass@1, max reasoning effort | DeepSeek-V4.1-Flash model card (Hugging Face) |
| DeepSeek V4 Pro | GPQA Diamond | 90.1 | V4-Pro (Preview) Max, pass@1 | Hugging Face model card (DeepSeek-V4-Pro) |
| DeepSeek V4.1 Flash | Humanity's Last Exam | 36.8 | Pass@1, no tools, max effort (text-only subset: 39.1) | DeepSeek-V4.1-Flash model card (Hugging Face) |
| DeepSeek V4 Pro | Humanity's Last Exam | 42.7 | V4-Pro-0813, no tools | Hugging Face model card (DeepSeek-V4-Pro-0813) |
| DeepSeek V4.1 Flash | Humanity's Last Exam (with tools) | 63.9 | Pass@1, with tools, max effort | DeepSeek-V4.1-Flash model card (Hugging Face) |
| DeepSeek V4 Pro | Humanity's Last Exam (with tools) | 60.0 | V4-Pro-0813, with tools | Hugging Face model card (DeepSeek-V4-Pro-0813) |
| DeepSeek V4.1 Flash | Terminal-Bench | 90.6 | Terminal-Bench 2.1, Pass@1, max effort | DeepSeek-V4.1-Flash model card (Hugging Face) |
| DeepSeek V4 Pro | Terminal-Bench | 87.9 | Terminal-Bench 2.1, V4-Pro-0813, max effort, DeepSeek Harness | Hugging Face model card (DeepSeek-V4-Pro-0813) |
| DeepSeek V4.1 Flash | LMArena Text Elo | 1476 | LMArena text overall, 'DeepSeek-V4.1-Flash-20260910 (Max)', ±6, as of 2026-10-27 | Arena (LMArena) text leaderboard |
| DeepSeek V4 Pro | LMArena Text Elo | 1465 | DeepSeek-V4-Pro (High, 20260813), ±7, board dated 2026-10-27 | LMArena (arena.ai) text leaderboard |
Scores are published results from model cards, lab reports, and public leaderboards, each linked to its source. Settings such as thinking mode or test version differ between sources and are shown next to each score. OpenLLM Buddy catalog models are uncensored fine-tunes; their scores are those of the official base model. Data collected 2026-10-30. How the index works