GoldieBench deep dive
DeepSeek V4 Flash's full benchmark breakdown.
DeepSeek's cheap tier, retrained for agents — same size, sharper loops. Every number below is either one of my own judged one-shot builds - playable on this site - or an outside result with its source linked. Nothing display-only, nothing vibes.
01 · The headline numbers
No scored tasks yet - this model is on the bench but unranked.
02 · Every benchmark, bar by bar
All 0 scored tasks, best first. Hover for the judge's comment; click through for every model's build on that task. Or overlay other models in the interactive graphs.
03 · Where it wins - with the judge's own words
04 · Where it struggles - quoted, not hidden
Boards that hide the weak rows are brochures. These are DeepSeek V4 Flash's lowest scored builds, verdicts unedited:
Nothing under 8.0 on the board right now - DeepSeek V4 Flash's floor is unusually high.
05 · Category breakdown vs the whole field
Games (0 tasks)
Others (0 tasks)
Pages (0 tasks)
Sims (0 tasks)
Visuals (0 tasks)
06 · Outside signals - every row sourced
My bench measures one thing: judged one-shot builds. These outside rows measure other things - kept separate, never blended into the GoldieBench average, every value linked to where it comes from.
No externally sourced rows tracked for this model yet - the GoldieBench scores above are the record.
07 · Head-to-head records
Not enough shared scored tasks yet.
08 · Methodology + honest limits
Every GoldieBench score is a one-shot, single-file build from an identical prompt - no retries, no hand-fixing - rendered for real, screenshotted, and scored 0-10 by one judge model on one rubric across the whole field. Failures score as failures. What this bench does NOT measure: multi-turn agent work, long-context recall, or API latency - that is what the sourced outside rows are for. Full method: /methodology.
Frequently asked questions
01How much does DeepSeek V4 Flash cost?
Benched on the DeepSeek-V4-Flash-0731 public beta, launched 2026-07-31 on DeepSeek's official API. DeepSeek describe it as a major upgrade to agent capabilities whose benchmark scores now surpass their previous V4-Pro-Preview, using the exact same model architecture and size as the preview — the gain is post-training, not scale. Natively supports the Responses API format and is adapted for Codex-style coding loops. Benched against api.deepseek.co
Source ledger
- 01Official vendor site: api-docs.deepseek.comapi-docs.deepseek.com
Every model's breakdown
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.