
Real head-to-head · same prompt, one shot
Claude Sonnet 5 vs DeepSeek V4 Pro
The agentic SWE frontier — 82% SWE-bench Verified, Dev Team mode. vs DeepSeek's flagship tier — benched head-to-head against its own cheap Flash.
What I tested — same prompt, two models
I run the same fixed prompt set through every new model the day it drops — same string, one shot, single HTML file out — and I score the result 0–10 on whether it ran, how close it hit the brief, and how good it looked. Below is what came out when I gave the exact same prompts to Claude Sonnet 5 and DeepSeek V4 Pro, side by side, on 47 shared tasks inside the Agent Operating System.
Both models were given identical prompts inside the Agent Operating System — no help, no iteration, no "best of N" tricks. I run each prompt once, save the HTML file the model produces, and score it 0–10 on whether it ran, how close it hit the brief, and how good it looked. The scoring is mine. The verdicts below are pulled from my source comparison guides at agentos.guide where I publish every score and the reasoning behind it.
Claude Sonnet 5 · Reach for it in Agent OS when the job is iterative, tool-using software engineering. For one-shot visual builds, GLM 5.2 (free) beat it 4-1 here.
DeepSeek V4 Pro · Benched on all 50 GoldieBench tasks via api.deepseek.com with the same pipeline as the Flash 0731 run, then published as a live side-by-side: goldiebench.com/vs-live/deepseek-flash-vs-pro.html loads both builds of every task in twin panes.
Side-by-side on 50 shared tasks
Click any cell to play that model's actual one-shot attempt. Medals are derived from my 0–10 scores per task (highest = 🥇, second = 🥈, third = 🥉).
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Strengths & weaknesses I logged
Claude Sonnet 5
Strengths
- 82.1% SWE-bench Verified — first model past 80% on real GitHub-issue repair
- Dev Team multi-agent mode + 1M context for repo-level agentic work
- Precision on hard logic — won the raycaster the open-weight field kept botching
Trade-offs
- One-shot creative-visual builds trail GLM 5.2 here (lost 4 of 5) — no iteration to catch its own bugs
- A temporal-dead-zone bug blanked its N-body orbit sim on the first shot
DeepSeek V4 Pro
Strengths
- Flagship reasoning tier on the same official API and 1M context as Flash
- Ran the identical 50-prompt set as V4 Flash 0731 — a clean same-vendor A/B
- Reasoning-first: thinks before writing every build
Trade-offs
- Unranked — builds are on the bench but not yet scored by the Opus vision judge
- Slower and pricier per build than Flash — the whole question is whether that buys quality
Pricing & context — the spec sheet
| Spec | Claude Sonnet 5 | DeepSeek V4 Pro |
|---|---|---|
| Vendor | Anthropic | DeepSeek |
| Context window | 1,000,000 tokens | 1,000,000-token context window |
| Price | $3 / $15 per M ($2/$10 intro) | API · pro tier |
| Pricing detail | $3.00 input / $15.00 output per million tokens; introductory $2.00/$10.00 through 2026-08-31. | DeepSeek's flagship tier, benched on `deepseek-v4-pro` via api.deepseek.com — the exact same 50 one-shot prompts, skill-infused game prompt and pipeline as the V4 Flash 0731 run, so the two runs are directly comparable side by side. DeepSeek's own line on the 0731 Flash refresh is that its post-training now beats the older V4-Pro-Preview — this run tests the current Pro against that claim. |
| Release | 2026-06-30 | 2026-07 |
| Bench coverage | 47/47 scored · avg 7.01/10 | 0/50 scored · avg — |
The verdict — which should you pick?
Not enough scored shared tasks yet for a head-to-head average. The live demos for both are on the matrix above — play them and form your own opinion.
If you only run one of these inside your stack, the head-to-head average above is the call. If you can run both, my honest play is to wire Claude Sonnet 5 and DeepSeek V4 Pro both into the Agent Operating System and dispatch each from the kanban by task type — agentic software engineering — write / run / test / fix loops on real repos → Claude Sonnet 5, checking whether deepseek's pro tier is worth the premium over flash 0731 → DeepSeek V4 Pro. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — Claude Sonnet 5 vs DeepSeek V4 Pro
Which is better, Claude Sonnet 5 or DeepSeek V4 Pro?
On Goldie Bench, Claude Sonnet 5 averages no scored verdicts yet across the shared tasks, with 0 gold, 0 silver, 4 bronze overall. DeepSeek V4 Pro averages no scored verdicts yet, with 0 gold, 0 silver, 0 bronze. Not enough scored shared tasks yet to call a winner.
How much does Claude Sonnet 5 cost vs DeepSeek V4 Pro?
Claude Sonnet 5: $3.00 input / $15.00 output per million tokens; introductory $2.00/$10.00 through 2026-08-31. DeepSeek V4 Pro: DeepSeek's flagship tier, benched on `deepseek-v4-pro` via api.deepseek.com — the exact same 50 one-shot prompts, skill-infused game prompt and pipeline as the V4 Flash 0731 run, so the two runs are directly comparable side by side. DeepSeek's own line on the 0731 Flash refresh is that its post-training now beats the older V4-Pro-Preview — this run tests the current Pro against that claim.
What's the context window for Claude Sonnet 5 vs DeepSeek V4 Pro?
Claude Sonnet 5 has a 1,000,000 tokens context window. DeepSeek V4 Pro has a 1,000,000-token context window context window.
When should I pick Claude Sonnet 5 over DeepSeek V4 Pro?
Pick Claude Sonnet 5 for: Agentic software engineering — write / run / test / fix loops on real repos; Repo-level reasoning across a 1M-token context (Dev Team multi-agent mode); Precise logic — raycasters, physics — where one-shot open models slip. The trade-off is the weaknesses we logged on the bench: One-shot creative-visual builds trail GLM 5.2 here (lost 4 of 5) — no iteration to catch its own bugs; A temporal-dead-zone bug blanked its N-body orbit sim on the first shot.
When should I pick DeepSeek V4 Pro over Claude Sonnet 5?
Pick DeepSeek V4 Pro for: Checking whether DeepSeek's pro tier is worth the premium over Flash 0731; Hard single-shot builds where extra reasoning depth may pay off. The trade-off is the weaknesses we logged on the bench: Unranked — builds are on the bench but not yet scored by the Opus vision judge; Slower and pricier per build than Flash — the whole question is whether that buys quality.
How does Goldie Bench score Claude Sonnet 5 vs DeepSeek V4 Pro?
Every demo on this page was built by Julian Goldie inside the Agent Operating System — same fixed prompt for both models, one shot, single HTML file out. Each result gets a 0–10 score on whether it ran, how close it hit the brief, and how good it looked. The highest score on each task gets gold; second gets silver; third gets bronze. See methodology for full provenance.
Related comparisons
Other head-to-heads using the same scoring system:
Claude Sonnet 5 vs Fusion DeepSeek V4 Pro vs Fusion Claude Sonnet 5 vs Claude Opus 5 DeepSeek V4 Pro vs Claude Opus 5 Claude Sonnet 5 vs Hermes MoA DeepSeek V4 Pro vs Hermes MoA Claude Sonnet 5 vs GPT-5.6 Sol DeepSeek V4 Pro vs GPT-5.6 SolFull model pages: Claude Sonnet 5 · DeepSeek V4 Pro · back to the leaderboard
The same stack Julian uses
Run this stack yourself.
Every demo on this bench was built inside the Agent Operating System — one prompt, one shot, single HTML file out. The Agent OS, the prompts, the templates, the weekly walkthroughs and 4,000+ founders shipping with it every day all live inside the AI Profit Boardroom.
4,000+founders
258documented wins
38countries
$59/momonthly














































