DeepSeek · mit

DeepSeek-V3.2 (Non-thinking)

DeepSeek-V3.2 (Non-thinking) by DeepSeek appears in 1 source with LLM Stats Code Index (estimated from arena) at 22.77 score. Best read for Low cost, Open weights.

CreatorDeepSeek

Release date2025-12-01

Knowledge cutoffNot published

Context131K tokens

Input price$0.28/M tokens

Output price$0.42/M tokens

Modalitytext

CountryCN

Metrics

All source-backed metrics

Open in leaderboard

LLM Stats Rank48ranking · source_rank

LLM Stats Code Index (estimated from arena)22.77 scoremetric

Code Arena969.31 %coding · coding_arena_score

Context131,072 tokenscontext · context

Speed336.25 c/sperformance · throughput

Latency1,927.45 msperformance · latency

Input price0.28 $/Mpricing · input_price

Output price0.42 $/Mpricing · output_price

Parameters685,000,000,000 paramsmodel · params

Evidence

Citations and source overlap

LLM StatsPublic full LLM leaderboard advanced explorer snapshot, including ranking, benchmark indexes, pricing, speed, context, license, and model metadata.Retrieved 2026-06-01

FAQ

How should I read this profile?

Treat this as a source-backed model dossier, not an EvalKit-run verification. The public values are replicated from linked sources and kept source-scoped.

Is DeepSeek-V3.2 (Non-thinking) verified by EvalKit?

No. EvalKit currently shows 0 verified rows until real run evidence exists.

Why can metrics disagree?

Different sources test different tasks, dates, prompts, and aggregation methods. EvalKit keeps those differences visible instead of merging them into a fake universal score.