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DeepSeek50SolidBenchmark pendingLow-cost reasoning and coding assistant / API model optionVerified 2026-06-09

Dossier · General AI assistant

DeepSeek

Low-cost reasoning and coding assistant / API model option · last verified 2026-06-09

Solid

General AI assistant

DeepSeek

50/100

ROLELow-cost reasoning and coding assistant / API model option

Editorial fit

Source quality

Citation honesty

Privacy controls

Value for money

Speed

FREEVerified 2026-06-07

FREEFree

CUSTOMPro

SolidVerified 2026-06-09VP·METHOD

DeepSeek flagship-ready dossier: Low-cost reasoning and coding assistant / API model option.

What is DeepSeek?

DeepSeek is a tool in the VerdictPal General AI assistant set: Low-cost consumer chat and API model provider for reasoning, coding, and OpenAI-/Anthropic-compatible model routing, with unusually low token prices and important privacy, residency, and institutional-risk caveats. It scores 50 out of 100 on editorial fit.

Role: Low-cost reasoning and coding assistant / API model optionCategory: General AI assistantEditorial · hands-on

DeepSeek at a glance, with the date each field was checked.
Field	Value
Editorial fit	50 out of 100
Dossier status	Solid
Set	General AI assistant
Role in a workflow	Low-cost reasoning and coding assistant / API model option
Pricing	Verified 2026-06-07 Free · Free Free · Pro Custom
Training on your data	Not recorded as a plan-wide guarantee. Check the dossier's privacy notes and sources.
Last verified	2026-06-09

Editor's note

Desk hands-on 2026-06: The models can be fine on price; the consumer web app is what we would not recommend — trust, transparency, and platform polish lag the API story by a mile.

Public facts · vendor & repo

List prices and pay-as-you-go entry points we can cite without running our own bench. Each tile links to a source when possible.

General AI assistantSetVerdictPal tool ↗

synthesizedEvidenceQuality gate ↗

8Sources checkedSources ↗

2026-06-07Pricing checkedQuality gate ↗

Limits & product surface

Non-price vendor claims — multipliers, caps, and API scope. Detailed matrices live in subscription and SDK sections below.

Primary surface: consumer-appTool identity ↗
Modalities: text, codeTool identity ↗
Workflow roles: [object Object], [object Object], [object Object]VerdictPal editorial ↗
Alternatives tracked: ChatGPT, Claude, Gemini, OpenRouter, QwenVerdictPal comparison set ↗

How it works · agent loop

The public positioning for this product — the loop we score against on VerdictPal.

Start with the wedge

Cost-sensitive API experiments where token price matters more than ecosystem polish

Run the representative task

Run 20 reasoning/coding tasks on V4-Flash, V4-Pro, ChatGPT, Claude, Gemini, and OpenRouter routes.

Check the failure modes

Privacy/residency may be unacceptable institutionally

Compare before recommending

Compare against ChatGPT, Claude, Gemini before shipping advice.

Who it fits, where it fails

Best for

Cost-sensitive API experiments where token price matters more than ecosystem polish
Coding and reasoning comparisons against ChatGPT, Claude, Gemini, Mistral, and OpenRouter routes
Developers who want OpenAI-/Anthropic-compatible endpoints for inexpensive model routing tests
Users who can keep sensitive or unpublished research out of consumer chat and standard API calls

Avoid if

Your institution bars sending research data to China-based AI services
You need clear enterprise data-residency, retention, or no-training guarantees for consumer chat
You want the most mature assistant ecosystem, integrations, admin controls, or procurement story
You cannot monitor model-name deprecations and API compatibility changes

Strengths

OpenAI- and Anthropic-compatible API
base URLs for both formats
V4-Flash and V4-Pro
thinking/non-thinking modes
1M context
384K max output
JSON output
tool calls
chat prefix completion beta
FIM completion beta in non-thinking mode
supported by agent/coding tools like Claude Code, GitHub Copilot, and OpenCode as backend model
low token pricing
high concurrency limits

Weaknesses

Privacy/residency may be unacceptable institutionally
Consumer and API terms differ
Geopolitical/export-control context can affect access
Very high max output can cause runaway generation if max_tokens is not set
Legacy model names deprecate 2026-07-24
DeepSeek reserves right to adjust prices; docs need monitoring

How it could improve

Institutional policy friction could be reduced with a local/on-prem deployment option, or at minimum with clear data-handling documentation that compliance teams can review without an NDA.
Editorial fit scores 50/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.
Wedge task fit scores 48/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.
Cost-to-value scores 45/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.
Opportunity cost scores 52/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.
Source grounding scores 54/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.
Privacy posture scores 22/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.
Reliability scores 48/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.
Competitive position scores 52/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.

Search modes · 4 lenses

One input box, many retrieval postures. Filter by tier.

01Free

Default

Default path for DeepSeek — verify limits on the live product.

02Pro

Deep work

Deep work path for DeepSeek — verify limits on the live product.

03Pro

Focused task

Focused task path for DeepSeek — verify limits on the live product.

04Free

Export & share

Export & share path for DeepSeek — verify limits on the live product.

Competitive lens

Where DeepSeek wins for cited research — and where a rival still belongs in the stack.

DeepSeek is stronger when cost-sensitive api experiments where token price matters more than ecosystem polish; ChatGPT may still win for narrower fit, procurement, or specialist depth.

DeepSeek

Cost-sensitive API experiments where token price matters more than ecosystem polish
Coding and reasoning comparisons against ChatGPT, Claude, Gemini, Mistral, and OpenRouter routes

ChatGPT

Your institution bars sending research data to China-based AI services
You need clear enterprise data-residency, retention, or no-training guarantees for consumer chat

Scores and evidence

Metric lab · 16 dimensions

Click a tile for the editorial note. Color follows score: coral, yellow, mint.

Shape

Avg 58 · 22–98

50Editorial fit

Weighted roll-up across 13 dimensions for General AI assistant; pending desk verification if rescored from public facts.

By group

Fit53

Editorial fit50
Wedge task fit48
Feature depth62

Cost51

Free-tier utility55
Cost-to-value45
Opportunity cost52

Trust64

Source grounding54
Privacy posture22
Failure transparency88
Evidence strength58
Transparency98

Workflow58

Integration reach55
Setup friction68
Reliability48
Competitive position52
Data portability65

Benchmark ledger

Public rows are vendor or third-party claims we logged with a date. Desk rows are reserved for VerdictPal self-run results.

Measure	Result	Source
Run 20 reasoning/coding tasks on V4-Flash, V4-Pro, ChatGPT, Claude, Gemini, and OpenRouter routescorrectness, tool-call quality, code pass rate, cost per solved task, latency, retry rate.	Planned2026-06-09	VerdictPal benchmark plan
Test a controlled 200K / 500K / 1M-token retrieval and summarization workloadfactual retention, quote accuracy, output completeness, latency, cost, failure rate.	Planned2026-06-09	VerdictPal benchmark plan
Swap OpenAI and Anthropic SDK configurations to DeepSeek base URLsintegration friction, streaming, tool calls, JSON mode, error semantics, deprecation warnings.	Planned2026-06-09	VerdictPal benchmark plan
Compare privacy, terms, residency, and policy constraints against ChatGPT, Claude, Gemini, and Mistraldata-use clarity, subprocessor clarity, enterprise controls, jurisdiction risk, allowed-use constraints.	Planned2026-06-09	VerdictPal benchmark plan

Editorial evidence · 0 entries

No editorial benchmark yet. The tool stays at status Solid until evidence lands.

This tool is in the VerdictPal Citation Fidelity protocol — frozen question bank, dual-reviewer grading, results still pending. Citation Fidelity v0.1 →

Benchmark coverage · 12 benchmarks

AIME ⚠ARC-AGI LMArena (Chatbot Arena)Citation Fidelity (VerdictPal Lab)CritPt FrontierMath HumanEval ⚠LiveBench MATH ⚠MMLU-Pro ⚠MMLU ⚠Vals Index ⚠

Benchmarks that evaluate or report on this tool. Scores and caveats live on the benchmark page.

Test scenarios · hands-on lab

How we exercised the product. Step through each run before you trust the scores.

Test run

Step 1 of 4

Start from the persona in best-for item 1.

Research log · desk notes

What we learned while building this dossier — not vendor copy.

2026-06-07Notion Tool pipeline (Card pipeline) ↗

Notion research pass

DeepSeek is the low-cost reasoning/API tool. This pass sharpens the key facts: DeepSeek’s API is OpenAI- and Anthropic-compatible, current V4-Flash/V4-Pro pricing is extremely low, context length is listed at 1M, and legacy deepseek-chat / deepseek-reasoner names are being deprecated. The low price is real, but the editorial warning is bigger than usual: privacy, residency, institutional policy, and geopolitical availability need explicit review.

2026-06-09VerdictPal git ↗

Flagship-ready structure

Converted imported research into metrics, panes, scenarios, benchmark rows, comparison notes, and pricing deck.

What it costs, what it keeps

Pricing deck · checked 2026-06-09

Pro

Custom

month

Fallback tier inferred from the imported pricing summary; verify live checkout before publication.
Verify live regional checkout before publishing procurement advice.

RAW · checked 2026-06-09: Verified 2026-06-07 from official DeepSeek API docs: V4-Flash $0.0028/1M cache-hit input, $0.14/1M cache-miss input, $0.28/1M output; V4-Pro $0.003625/1M cache-hit input, $0.435/1M cache-miss input, $0.87/1M output. Both list 1M context, max 384K output, JSON output, tool calls, chat prefix beta, FIM beta in non-thinking mode, and OpenAI/Anthropic base URLs. Concurrency limits: 2500 Flash, 500 Pro. deepseek-chat and deepseek-reasoner deprecate 2026-07-24 15:59 UTC.

Privacy deep-dive · checked 2026-06-09

DeepSeek consumer chat and Open Platform/API are separate governance surfaces. Privacy policy notes downstream apps built on the open platform are controlled by their developers. Review DeepSeek privacy, open-platform terms, model/training disclosures, and local policy before sending unpublished or regulated data.

Under the hood

Vendors named on the product about page — useful for procurement and privacy reviews.

low-cost reasoning: DeepSeek
coding assistance: ChatGPT
API model routing: Claude

Alternatives and context

Alternatives

ChatGPT Claude Gemini OpenRouterQwen

Head-to-head

DeepSeek vs ChatGPT DeepSeek vs Claude DeepSeek vs Gemini DeepSeek vs OpenRouter

Compare side-by-side → open compare

Workflow roles

How this tool fits into a composed research stack:

low-cost reasoningcoding assistanceAPI model routing

Powered by

The model(s) that drive this tool. The tool is the wrapper; the model is the engine.

Deep panes · 6 lenses

Editorial lenses only. Subscription and API pricing live in their own sections above.

Lens 01

Positioning

DeepSeek is framed here as Low-cost reasoning and coding assistant / API model option. DeepSeek is the low-cost reasoning/API tool. This pass sharpens the key facts: DeepSeek’s API is OpenAI- and Anthropic-compatible, current V4-Flash/V4-Pro pricing is extremely low, context length is listed at 1M, and legacy `deepseek-chat` / `deepseek-reasoner` names are being deprecated. The low price is real, but the editorial warning is bigger than usual: privacy, residency, institutional policy, and geopolitical availability need explicit review.

Checked: 2026-06-07
Evidence: synthesized

Cost-sensitive API experiments where token price matters more than ecosystem polish
Coding and reasoning comparisons against ChatGPT, Claude, Gemini, Mistral, and OpenRouter routes
Developers who want OpenAI-/Anthropic-compatible endpoints for inexpensive model routing tests
Users who can keep sensitive or unpublished research out of consumer chat and standard API calls

Sources and provenance

Source ledger · 8 checked

Product sitechecked 2026-06-07
Chatchecked 2026-06-07
API docschecked 2026-06-07
API pricingchecked 2026-06-07
API changelogchecked 2026-06-07
FAQchecked 2026-06-07
Privacy policychecked 2026-06-07
Open Platform termschecked 2026-06-07

Quality gate · Solid

Evidence ready

Benchmark pending

Verdict history

2026-06-07DeepSeek is the low-cost reasoning/API tool. This pass sharpens the key facts: DeepSeek’s API is OpenAI- and Anthropic-compatible, current V4-Flash/V4-Pro pricing is extremely low, context length is listed at 1M, and legacy deepseek-chat / deepseek-reasoner names are being deprecated. The low price is real, but the editorial warning is bigger than usual: privacy, residency, institutional policy, and geopolitical availability need explicit review.
2026-06-09Converted imported Notion research into a full flagship-ready dossier template with metrics, panes, pricing deck, scenarios, benchmark rows, and comparison slices.

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Questions this dossier answers

Every answer below is assembled from the dated fields on this page. Nothing is written separately for search.

Is DeepSeek worth using?

DeepSeek scores 50 out of 100 on editorial fit and carries Solid dossier status. Its job in a research workflow is: Low-cost reasoning and coding assistant / API model option.

Who is DeepSeek best for?

DeepSeek earns its place when you need:

Cost-sensitive API experiments where token price matters more than ecosystem polish
Coding and reasoning comparisons against ChatGPT, Claude, Gemini, Mistral, and OpenRouter routes
Developers who want OpenAI-/Anthropic-compatible endpoints for inexpensive model routing tests
Users who can keep sensitive or unpublished research out of consumer chat and standard API calls

When should you not use DeepSeek?

Skip DeepSeek in these cases:

Your institution bars sending research data to China-based AI services
You need clear enterprise data-residency, retention, or no-training guarantees for consumer chat
You want the most mature assistant ecosystem, integrations, admin controls, or procurement story
You cannot monitor model-name deprecations and API compatibility changes

What does DeepSeek cost?

Verified 2026-06-07 Free · Free Free · Pro Custom. Pricing last checked 2026-06-09.

Does DeepSeek train on your data?

Not recorded as a plan-wide guarantee. Check the dossier's privacy notes and sources.. Privacy terms last checked 2026-06-09.

What goes wrong with DeepSeek?

The dossier publishes 6 failure modes for DeepSeek, and they stay published whether or not the vendor likes them:

Privacy/residency may be unacceptable institutionally
Consumer and API terms differ
Geopolitical/export-control context can affect access
Very high max output can cause runaway generation if max_tokens is not set
Legacy model names deprecate 2026-07-24
DeepSeek reserves right to adjust prices; docs need monitoring

What are the alternatives to DeepSeek?

The closest options to DeepSeek are ChatGPT, Claude, Gemini, OpenRouter, Qwen. Each one that has a tool in the atlas is linked from this dossier, with a head-to-head comparison.

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Info

Quality gate

Evidence ready
Benchmark pending
Pricing checked 2026-06-09
Privacy checked 2026-06-09

Evidence

Editorial · hands-on

8 sources · 4 bench entries

Verdict history

2026-06-07DeepSeek is the low-cost reasoning/API tool. This pass sharpens the key facts: DeepSeek’s API is OpenAI- and Anthropic-compatible, current V4-Flash/V4-Pro pricing is extremely low, context length is listed at 1M, and legacy deepseek-chat / deepseek-reasoner names are being deprecated. The low price is real, but the editorial warning is bigger than usual: privacy, residency, institutional policy, and geopolitical availability need explicit review.
2026-06-09Converted imported Notion research into a full flagship-ready dossier template with metrics, panes, pricing deck, scenarios, benchmark rows, and comparison slices.