DeepSeek V4-Pro vs Claude Sonnet 4.6: one point apart, 10× apart

The open-weight challenger outscores the closed daily driver on paper. The price sheet isn't the whole story.

By the benchr team · · View changelog · Figures verified against official sources, June 10, 2026

V4-Pro input / 1MDeepSeek · output $0.87
Sonnet input / 1MAnthropic · output $15
V4-Pro SWE-benchVerified, official card
Sonnet SWE-benchVerified, official

This is the comparison that decides whether the open-weight tier has earned your production traffic. One point of SWE-bench separates these two — in DeepSeek's favor — while an order of magnitude separates the bills. The interesting question isn't which model is better. It's whether the things Sonnet still does better are the things your workload needs.

Side-by-side specs

DeepSeek V4-Pro vs Claude Sonnet 4.6 — verified figures, June 10, 2026
DimensionDeepSeek V4-ProClaude Sonnet 4.6
Input / 1M$0.435$3.00
Output / 1M$0.87$15.00
Cache-hit input / 1M$0.0036$0.30
Context window1,000,0001,000,000
Max output384,00064,000
SWE-bench Verified80.6%79.6%
GPQA Diamond90.1%89.9%
LicenseMIT (self-hostable)Proprietary API only

The bill, on a real pipeline

A document-processing pipeline that ingests 50M input tokens and produces 8M output tokens a month: Sonnet 4.6 charges $150 for input and $120 for output — $270/month versus $21.75 + $6.96 = $28.71 on V4-Pro. Multiply both by ten for a serious pipeline and the gap is $2,700 against $287. DeepSeek's cache-hit rate ($0.0036/1M) makes repeated-prefix workloads cheaper still — effectively free input on stable prompts.

What Sonnet still buys you

Three real things, none of them on the price sheet. First, agent-loop discipline: in long multi-step tool use, Claude recovers from errors with less scaffolding — the gap the open-weight survey calls a lead rather than a chasm, but a lead all the same. Second, the compliance story: Anthropic's API terms, vision support, and safety tuning fit enterprise review processes that DeepSeek's hosted API often doesn't pass. Third, max-context honesty under load — though DeepSeek now publishes its own long-context numbers (83.5% MRCR at 1M), which is more than most rivals do.

The self-host escape hatch

If the objection to DeepSeek is "our data can't go to that API," the MIT license is the counter: download the weights and serve V4 yourself. You trade per-token fees for GPU costs and ops work — the local-inference piece walks the math. Sonnet has no equivalent. For regulated environments, that one row of the table can decide the whole comparison.

Frequently asked

Is DeepSeek V4-Pro really 17 times cheaper than Sonnet 4.6 on output?

Yes — $0.87 vs $15.00 per million output tokens, both from official pricing pages. Input is 7 times cheaper ($0.435 vs $3.00). On benchmarks the two sit a point apart: V4-Pro posts 80.6% SWE-bench Verified to Sonnet's 79.6%.

What do you give up for the lower DeepSeek price?

Three things. Tool-use polish inside long agent loops, where Claude's tuning is still ahead. The data story — DeepSeek's hosted API runs on its own infrastructure with lighter safety tuning, which some compliance teams can't accept. And vision: Sonnet 4.6 handles images; check V4's current multimodal support on the official card before assuming parity.

Can I self-host DeepSeek V4 instead of using the API?

Yes. The weights are MIT-licensed, so you can run V4 on your own hardware with no per-token fee — that's the strongest answer to data-residency concerns, at the cost of serving infrastructure. Sonnet 4.6 has no self-host option.

Changelog

  • June 10, 2026 — Expanded from a spec table into a full comparison: cost math on a concrete workload, where each model wins, and a verdict. Page re-indexed.
  • June 6, 2026 — Published as a spec-table stub (noindexed pending expansion).

Sources

  • DeepSeek pricing — api-docs.deepseek.com/quick_start/pricing (verified June 10, 2026)
  • DeepSeek-V4-Pro model card — huggingface.co/deepseek-ai/DeepSeek-V4-Pro (verified June 10, 2026)
  • Anthropic pricing — platform.claude.com/docs (verified June 10, 2026)
  • benchr model-figures.json — the verified figure record (June 10, 2026)