Use DeepSeek V3.2 in Tabbit

Use in Tabbit DeepSeek V3.2

DeepSeek V3.2 · Model overview

Check the evidence before choosing a workflow

A compact view of reviewed task guides, public evaluations, and evidence boundaries. Client access still depends on your current account.

Official source

Task guides2

Review sources4

Sources reviewed0

Editor picks6

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All prompts and workflows

API configuration · Agent workflowUnverified

DeepSeek V3.2 Thinking Tool Calls and Multi-turn State Configuration

V3.2 integrates thinking directly into tool use. Multi-turn tool requests must fully pass back the previous turn's `reasoning_content`; otherwise, the API may return an error or lose the reasoning state. The thinking mode should not be configured with temperature/top_p.

Prepare: API key, tool schema, message state, reasoning_content
Runtime: DeepSeek OpenAI-compatible Chat Completions

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Agent workflow · reasoningUnverified

DeepSeek-V3.2's Long-Context and Agent Evidence-Anchoring Workflow

DeepSeek's technical report shows that V3.2 uses large-scale environment and complex-instruction synthesis to train Agent generalization; when using it, organize tool results, task constraints, and verifiable outcomes into a trajectory instead of relying on a single “please think autonomously” instruction.

Prepare: source packet, tool outputs, constraints, verification target
Runtime: DeepSeek V3.2 retrieval and tool harness

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Read evidence and limits

Public results use different versions, tiers, and harnesses; unknown values stay unknown.

All reviews and sources

DeepSeek API Docs / DeepSeek-V3.2 ReleaseVendor report

DeepSeek-V3.2 Official Release: Reasoning and Agent Positioning of V3.2 and Speciale

V3.2 and Speciale, official release 2025-12-01; V3.2 App/Web/API with thinking and non-thinking tools, Speciale API-only and no tools at launch; full harness undisclosed.

Evidence: Vendor report
Boundary: does not merge Speciale competition results with V3.2 production success

Read evidence Original source

arXiv / DeepSeek-V3.2: Pushing the Frontier of Open Large Language ModelsEditorial analysis

DeepSeek-V3.2 Technical Report: DSA, Agent Synthetic Data, and Reasoning Baselines

V3.2 technical report v1 dated 2025-12-03; DSA, scalable RL, 1,800+ environments and 85k+ instructions; paper benchmarks differ from an API harness.

Evidence: Editorial analysis
Boundary: does not derive your success rate, latency, or cost from training scale

Read evidence Original source

SWE-bench LeaderboardsEditorial analysis

DeepSeek V3.2 Coding Agent Results on the SWE-bench Leaderboard

V3.2 high and Reasoner on mini-SWE-agent; entries dated 2026-02-17/2025-12-01, 70.00%/$0.45 and 60.00%/$0.03; Verified uses 500 instances, full logs undisclosed.

Evidence: Editorial analysis
Boundary: does not establish current pricing, general code quality, or tool-free success

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DeepSeek

Use DeepSeek V3.2 in Tabbit

Explore sourced prompt guides, evaluations, and community reports for DeepSeek V3.2—then use the model directly in Tabbit.