Models / DeepSeek V3.1 Terminus

DeepSeek V3.1 Terminus

MoE workstation
HuggingFace → HuggingBay → DeepSeek → Find for my hardware

685B total, ~37B active per token (MoE) - same backbone as DeepSeek V3. Instruct/agent-tuned variant of V3.1-Base: improves language consistency (less mixed Chinese-English) and adds Code Agent + Search Agent tool-use. FP8 quantization. Open weights under MIT.

AI-generated content marks

This model embeds text watermarks in generated text and adds C2PA provenance metadata to supported files such as .png, .jpg, and .svg. Marks can be lost through editing, screenshots, or format conversion, so their absence does not prove a file is human-made.

Provider transparency docs →

coding reasoning chat
Parameters
685.0B
Context
128k
License
mit
Developer
DeepSeek
Origin
🇨🇳 China
Released
Sep 2025

Scores

Coding
80
Reasoning
85
General
82

Score per dollar

304 pts per $/M input

general_score (82) divided by cheapest input price ($0.27/M). Higher is better value. See live pricing.

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Or run it in the cloud

Live per-provider pricing, throughput and uptime - refreshed about 19 hours ago via OpenRouter. Click a column to sort.

Provider Type Input $/M Output $/M Cache $/M Tok/s Latency Uptime Value
SiliconFlow
API 0.27 1.00 - - - 100.00% best uptime
StreamLake
API 0.34 1.03 - - - 100.00%

Default order: throughput among 95%+ uptime providers, then latency; subscriptions last. Sort by any column. Subscription rows show $/mo in the Value column - per-token columns are "-". Affiliate links are marked sponsored / nofollow. Confirm current pricing on the provider's site before committing.

Detailed API pricing page + JSON endpoint →

See who runs DeepSeek in production →

PRICE HISTORY

Inference cost over time

Data accumulates from the first daily sync - longer ranges populate over time. Prices come from OpenRouter snapshots, not a historical API.

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