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DeepSeek · open-weights

DeepSeek-V3.1-Terminus

DeepSeek-V3.1-Terminus is an open-weights language model from DeepSeek, released September 22, 2025. Its makers disclosed about 671B parameters.

What’s improved? Language consistency: fewer CN/EN mix-ups & no more random chars. Agent upgrades: stronger Code Agent & Search Agent performance. DeepSeek-V3.1-Terminus delivers more stable & reliable outputs across benchmarks compared to the previous version.

Check it against your own PC →

Lab
DeepSeek
Released
September 22, 2025
Weights
Open
Parameters
671B disclosed
Context
–
Price / M tokens
–
Epoch ECI
not yet rated

Can you run DeepSeek-V3.1-Terminus locally?

Even with 32 GB of VRAM and 32 GB of RAM it is too large to run at a usable speed on a single consumer GPU. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.

GPU memoryVerdictBest quantVRAMRAMtok/s
6 GB VRAMSize unknown––––
8 GB VRAMSize unknown––––
12 GB VRAMSize unknown––––
16 GB VRAMSize unknown––––
24 GB VRAMSize unknown––––
32 GB VRAMSize unknown––––

Parameter count unknown. The weights may not be on Hugging Face yet.

Benchmark results

Epoch AI has not published results for DeepSeek-V3.1-Terminus yet. New models are usually evaluated within days to weeks.

Links

Announcement

More from DeepSeek

DeepSeek V4.1 Flash 1017 · DeepSeek V4 Flash Vision Exp · DeepSeek V4.1 Flash · DeepSeek V4 Pro 0813 · DeepSeek V4 Flash 0731 · DeepSeek V4 Pro DSpark · DeepSeek V4 Flash DSpark · DeepSeek-V4-Pro

Data updated Thu, 12 Nov 2026 09:42 UTC. Benchmarks, Capabilities Index and model announcements: Epoch AI, “Capabilities & benchmarking” and “Data on AI models” (CC BY 4.0); category scores are ModelTape's own fit on Epoch's results. Releases and prices: models.dev (MIT). Sizes and quantizations: Hugging Face. “Runs on” figures are estimates from model size, quantization and memory bandwidth (±30–50%).
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