Head to head

Qwen3.8 27B vs DeepSeek V4.1 Flash

DeepSeek V4.1 Flash scores higher on 3 of the 3 benchmarks both models publish. The widest gap is on Terminal-Bench, where DeepSeek V4.1 Flash leads by 17.6 points. Both have open weights; Qwen3.8 27B is far lighter to host, needing about 19 GB at 4-bit against 381 GB for DeepSeek V4.1 Flash.

Qwen3.8 27BAlibaba Qwen · OpenLLM Buddy catalog83.2compositeDeepSeek V4.1 FlashDeepSeek · OpenLLM Buddy catalog79.8composite

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 Diamond
    89.290.9

    Pass@1, max reasoning effort

  • Humanity's Last Exam
    30.836.8

    Pass@1, no tools, max effort (text-only subset: 39.1)

  • Terminal-Bench
    73.090.6

    Terminal Bench 2.1 (Terminus harness)Terminal-Bench 2.1, Pass@1, max effort

  • LMArena Text Elo · not counted
    14361476

    LMArena text overall, 'Qwen3.8-27B', ±5, as of 2026-10-27LMArena text overall, 'DeepSeek-V4.1-Flash-20260910 (Max)', ±6, as of 2026-10-27

Should you pick Qwen3.8 27B or DeepSeek V4.1 Flash?

Pick Qwen3.8 27B if…

  • You want the lighter model to host: about 19 GB at 4-bit against 381 GB.
  • You want to run it locally: at 4-bit it fits one 24–32 GB consumer GPU.
  • You want it running in minutes on a dedicated GPU through OpenLLM Buddy, in an uncensored build.

Pick DeepSeek V4.1 Flash if…

  • You care most about Humanity's Last Exam, Terminal-Bench, where it scores at least 2 points higher.
  • People prefer its answers in blind chats: LMArena Elo 1476 against 1436.
  • You need fast responses: about 217 tokens per second through APIs, against 41.
  • Cost matters: $1.20 per million output tokens against $2.55.
  • You want it running in minutes on a dedicated GPU through OpenLLM Buddy, in an uncensored build.

Hardware and cost to run

Qwen3.8 27B

At 4-bit it needs about 19 GB, which fits a single RTX 4090, so it can run on a home workstation with llama.cpp, Ollama, or vLLM. Full BF16 precision needs about 62 GB (1× H100 (80 GB)).

On OpenLLM Buddy: Qwen3.8-27B-Uncensored-FP8 runs on H100 80GB as an FP8 build, with an OpenAI-compatible API and no per-token fees. Prices start at $53 USD for 11 hours.

Deploy Qwen3.8 27B
Full GPU memory table for Qwen3.8 27B

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 Flash
Full GPU memory table for DeepSeek V4.1 Flash

Category profile

Category index uses every test each model reports, not only the shared ones.

ReasoningCodingAgenticKnowledge
Qwen3.8 27BDeepSeek V4.1 Flash
Reasoning70.375.9
Coding81.972.1
Agentic—91.3
Knowledge97.3—

Specs side by side

Qwen3.8 27BDeepSeek V4.1 Flash
LabAlibaba QwenDeepSeek
WeightsOpenOpen
Released2026-08-142026-09-10
Parameters27B dense552B total, 16B active (MoE)
Context262K (up to 1M)1M
LicenseApache-2.0MIT
4-bit memory19 GB · RTX 4090 (24 GB)381 GB · 4× H200 (564 GB)
API price$0.425 in / $2.55 out per 1M tokens$0.300 in / $1.20 out per 1M tokens
API speed41 tok/s217 tok/s
One-GPU speed (est.)≈ 52–69 tok/s on H100 80GB (FP8)—

Related comparisons

Sources

ModelTestScoreSettingSource
Qwen3.8 27BGPQA Diamond89.2—Qwen3.8-27B model card (Hugging Face)
DeepSeek V4.1 FlashGPQA Diamond90.9Pass@1, max reasoning effortDeepSeek-V4.1-Flash model card (Hugging Face)
Qwen3.8 27BHumanity's Last Exam30.8—Qwen3.8-27B model card (Hugging Face)
DeepSeek V4.1 FlashHumanity's Last Exam36.8Pass@1, no tools, max effort (text-only subset: 39.1)DeepSeek-V4.1-Flash model card (Hugging Face)
Qwen3.8 27BTerminal-Bench73.0Terminal Bench 2.1 (Terminus harness)Qwen3.8-27B model card (Hugging Face)
DeepSeek V4.1 FlashTerminal-Bench90.6Terminal-Bench 2.1, Pass@1, max effortDeepSeek-V4.1-Flash model card (Hugging Face)
Qwen3.8 27BLMArena Text Elo1436LMArena text overall, 'Qwen3.8-27B', ±5, as of 2026-10-27Arena (LMArena) text leaderboard
DeepSeek V4.1 FlashLMArena Text Elo1476LMArena text overall, 'DeepSeek-V4.1-Flash-20260910 (Max)', ±6, as of 2026-10-27Arena (LMArena) 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