DeepSeek vs Claude for Coding

DeepSeek is the cheap, open-weights choice; Claude is the closed model with deeper tooling around it. On the API, DeepSeek's flash model costs $0.15 per million input tokens and $0.60 output at off-peak rates, while Claude Sonnet 5.5 costs $2 and $10. For coding, pick Claude when failures are expensive and DeepSeek when volume is high or you need weights you can host yourself. Prices checked 31 October 2026.

The short version

That is the decision for most readers. The sections below give the prices, the facts we could read on each vendor's pages, and the places where a pure price comparison misleads.

What each one is

DeepSeek

DeepSeek is a model lab with its own hosted API and a public model family. As of our check, the API lists two models. deepseek-flash is served by DeepSeek-V4.1-Flash-1017 and deepseek-v4-pro is served by DeepSeek-V4-Pro-0813. Both list a 1M-token context window and a maximum output of 384K tokens. Both support JSON output, tool calls, the Responses API and an Anthropic-compatible API. Only the flash model lists vision support.

The weights are public. The deepseek-ai/DeepSeek-V4-Pro repository on Hugging Face carries the license:mit tag, and sibling repositories for Flash and Flash-Base sit under the same organisation. If you want to run a model on your own hardware, this is the line that matters. You can read more on the DeepSeek models page.

Claude

Claude is Anthropic's closed model family. The current API lineup on the pricing page is Fable 5.1, Opus 5.5, Sonnet 5.5 and Haiku 5.5. You reach it through the Anthropic API, through Claude's own apps, and through cloud partners. There are no public weights. Read the Claude models page for the family.

The product around the model is a large part of the pitch. Claude Code, the agent Anthropic builds, is described in its docs as a tool that reads your codebase, edits files, runs commands and integrates with development tools. We compare it with other agents on the Claude Code page.

Prices side by side

All prices are per million tokens, taken from each vendor's pricing page on 31 October 2026.

Three details change how you read this table.

First, DeepSeek has a clock. Its pricing footnote says off-peak rates are half of peak rates. Peak hours are 01:00 to 04:00 and 06:00 to 10:00 UTC, Monday through Friday, excluding Chinese public holidays. Every other hour is off-peak, including weekends. If your jobs are batch work, you can schedule them into the cheap window. If your team works interactively during those hours, expect the peak rate.

Second, Haiku 5.5 is not far from DeepSeek flash on price. Anthropic's pricing page lists Haiku 5.5 from $0.10 input and $0.50 output. So the "DeepSeek is 10x cheaper" line only holds against Sonnet and above. Against Haiku the gap is small, and the question becomes quality on your task.

Third, cache behaviour differs. DeepSeek's cache-hit input price is a tiny fraction of the miss price. Claude cache reads are $0.10 per million on Sonnet 5.5, against $2 for uncached input. An agent loop re-sends a lot of context, so cache hits decide the real cost on both sides. We covered how that works for the two big Western vendors in Anthropic API vs OpenAI API.

What a coding task actually costs

The per-token price is only half the cost. An agent run is a loop: read files, call a tool, read the result, edit, run tests, repeat. Each turn re-sends the conversation, so input tokens dominate. A cheap model that needs three tries can cost more than a stronger model that needs one.

Here is a way to think about it without inventing numbers. Take any task you run often. Count the turns it takes with your current model. Count the retries. Multiply turns by the average context size and by the price per million. Do it once for each model, using the table above. The model with the lower per-token price wins only if its turn count and retry count stay close to the other's.

We are not publishing a benchmark of that comparison, because we did not run one. Published coding benchmarks exist, and we explain how to read them in the benchmarks section. The honest advice is to pick three real tasks from your own repo and run both models on them.

For DeepSeek, the V4-Pro model card reports 80.6 on SWE-bench Verified and 67.9 on Terminal-Bench 2.0 in Max mode, and V4-Flash reports 79.0 and 56.9. Those are vendor-reported. Anthropic's recent launch tables use Terminal-Bench 4.0, a different version, so we do not set the two sets of numbers side by side.

Using DeepSeek inside Claude Code

You do not have to choose one tool to choose one model. DeepSeek documents a path that points Claude Code at its API. The setup uses environment variables, and the base URL is DeepSeek's Anthropic-format endpoint.

export ANTHROPIC_BASE_URL=https://api.deepseek.com/anthropic
export ANTHROPIC_AUTH_TOKEN=<your DeepSeek API key>
export ANTHROPIC_MODEL=deepseek-flash[1m]
export CLAUDE_CODE_SUBAGENT_MODEL=deepseek-flash
claude

Those lines come from DeepSeek's own guide. The guide also sets the Opus, Sonnet and Haiku defaults to DeepSeek models, so every tier Claude Code asks for lands on a DeepSeek model. DeepSeek's Anthropic page adds a note that model names starting with claude are still accepted: claude-opus names map to deepseek-v4-pro, and other claude names map to the flash model.

There is a catch to plan for. When you do this, you are using Claude Code as the harness and DeepSeek as the brain. Anthropic's features that depend on its own models, such as the Claude subscription limits, do not apply, and you pay DeepSeek per token. Features that rely on Claude-specific behaviour may act differently. DeepSeek's Anthropic-format guide lists the gaps: deepseek-v4-pro does not process images and replaces them with [Unsupported Image], document and MCP content blocks are not supported, fields such as cache_control and budget_tokens are ignored, and tool_choice set to any is treated as auto.

DeepSeek also lists other agents in its integration guides, including Codex, OpenCode and OpenClaw. If you use OpenCode, read Claude Code vs OpenCode for how that tool treats model choice.

Open weights versus a closed service

The biggest structural difference is not the price. It is who holds the model.

Open weights give you three things. You can keep data inside your own network. You can pin a version, so a model update never changes your results overnight. And you can pick any host that serves it, which keeps price competition alive. The cost is hardware and operations. A 1M-context model of this size is not a laptop job. For the trade-offs in general, read open vs closed models.

Closed models give you a vendor who handles all of that, a single support path, and features that are built together with the model. You give up the ability to move the weights.

Per the model cards, V4-Pro has 1.6T total and 49B active parameters and V4-Flash has 284B total and 13B active, both with 1M context and an MIT license. The cards give no GPU memory figure.

Privacy and data handling

This is the section to read twice if you work with client code.

For DeepSeek, there are two separate questions. If you self-host the weights, your prompts never leave your servers, and the license on the weights is the only legal text that matters. If you use the hosted API, your prompts go to DeepSeek's servers and its terms apply. DeepSeek's privacy policy says it stores data in the People's Republic of China, keeps account data including inputs for as long as you have an account, and lists user input among the data it uses to train its models, with a right to opt out.

For Claude, Anthropic publishes a data-usage page in the Claude Code docs, and commercial customers have their own terms. Anthropic's Commercial Terms say it may not train models on Customer Content from the Services, and its privacy center says inputs and outputs are deleted from its backend within 30 days, with exceptions such as a zero data retention agreement. We cover the Claude Code side on the Claude Code agent page.

A practical rule: do not send regulated data to any hosted API until you have read its terms for your plan. For code that must not leave your network, the open-weights route is the only one of the two that fully keeps it in house.

Limits and gotchas

• Peak pricing. DeepSeek's cheap rates need off-peak timing. Interactive use during weekday mornings in UTC costs double.
• Concurrency. DeepSeek's pricing page lists concurrency limits of 2,500 for one model and 500 for the other. Check which is which on the page before sizing a batch job.
• Legacy names. deepseek-v4-flash still works but those requests are served by the newer flash model and billed at the flash price. Pin the name you mean.
• Vision. The Pro model lists vision as not supported. Flash supports it.
• Search and fetch calls. DeepSeek's server-side search and fetch calls through its harness, Claude Code or Codex are free for now, and per-request billing starts at 00:00 Beijing time on 1 November 2026. If you use them, your bill changes the day after our check date.
• Fast modes. Anthropic lists a fast mode for Opus 5.5 at twice standard pricing. DeepSeek has no equivalent on its pricing page.
• Currency of facts. Both vendors change prices and model names often. Treat this page as a snapshot and click through to the pricing page before you commit.

Who should pick which

A solo developer on a budget

Start with DeepSeek flash through your agent of choice, and run your jobs off-peak when you can. Keep a Claude plan for the tasks where the cheaper model stalls. Claude Pro is $20 a month on Anthropic's pricing page, and it is the way to use Claude Code without per-token billing.

A small team shipping product

Use Claude as the default and DeepSeek as a cost lever. Route bulk work, such as test generation, code summaries and first-draft refactors, to the cheap model. Keep the strongest model for review and the hard bug. Both vendors' APIs work with the same agent through the Anthropic-format endpoint, so the switch is an environment variable, not a rewrite.

A company with strict data rules

Look at self-hosting DeepSeek on your own or rented GPUs. Our hosting section lists providers, and the compare hosting tool lets you put them side by side. Run a pilot with a non-sensitive repo first. If self-hosting is more than your team can run, the choice becomes which vendor's commercial terms you trust, and that is a legal read, not a benchmark.

A team building an agent product

Keep the model behind one interface. Both vendors speak the Anthropic message format, so you can build against one client and swap the base URL. That keeps you free to chase price as it moves.

Our take

We think the sensible default for most coding teams is not either-or. It is Claude for the work where quality is the bottleneck and DeepSeek for the work where volume is. The price table makes the case for the second half plainly: at off-peak rates, DeepSeek flash input is roughly a thirteenth of Sonnet 5.5's, and output is a sixteenth. That gap is too large to ignore for batch work.

The case for the first half is softer, and we want to be straight about that. We did not run a head-to-head test for this page, and we are not going to quote benchmark numbers we could not read. What we can say from the documents is narrower. Claude Code is built by the same company that builds Claude, and its docs describe features such as skills, hooks and subagents as part of the product. DeepSeek's docs describe an API that works with that ecosystem rather than a competing agent. So the sensible reading is that DeepSeek is a model you plug in, and Claude is a model plus a product around it.

If you are choosing today, run the three-task test from the cost section. It takes an afternoon, and it is worth more than any table on this page, ours included.

Setup checklist

1. Create a DeepSeek API key on its platform and add a small balance. The pricing page says fees are deducted from your topped-up balance or granted balance, granted first.
2. Set the four environment variables above in a separate shell profile, so your normal Claude login stays untouched.
3. Pick three real tasks from your repo. Include one bug fix, one refactor and one new feature.
4. Run each task with DeepSeek flash, then with Claude Sonnet 5.5. Record turns, retries and the final token count from each tool's usage display.
5. Repeat the cheap runs at an off-peak hour and a peak hour to see the real price difference.
6. Decide per task type, not per vendor, and write down the rule you pick.

Related pages

• DeepSeek models and Claude models for the full families
• Compare models for the interactive table
• Open vs closed models for the weights question
• OpenRouter alternatives if you want one key for many models