Claude Opus 5.5 vs DeepSeek Flash (4.1)
Claude Opus 5.5 scores higher on the Models at Work leaderboard (91 vs 70 out of 100). DeepSeek Flash (4.1) is about 15× cheaper per blended million tokens ($0.52 vs $8).
| Claude Opus 5.5 · Anthropic | DeepSeek Flash (4.1) · DeepSeek | |
|---|---|---|
| Leaderboard rank | #1 | #9 |
| Score (0–100) | 91 | 70 |
| Tier | Frontier | Fast and cheap |
| Price per 1M tokens | $4 in · $20 out | $0.30 in · $1.20 out |
| Context window | 1M | 1M |
| Open weights | No | Not verified |
| Artificial Analysis Intelligence Index | 58 | — |
| Arena text score | 1507 | — |
| Humanity's Last Exam, Diamond (Scale) | 55.0 | — |
| Epoch Capabilities Index | 167 | — |
| Best for | Agentic coding, Long-running agents, Enterprise knowledge work | Cheap coding tiers, Bulk generation, Experiments where data residency is not a constraint |
Choose Claude Opus 5.5 if…
- you need agentic coding
- you need long-running agents
- you need enterprise knowledge work
The model people actually ship agents on: top of the independent index, a price that does not need a budget meeting, and a community that complains mainly about how much it has to be used.
Caveats: Arena puts Gemini 4 Argon ahead on chat preference; the gap is inside two scores' error bars.
Choose DeepSeek Flash (4.1) if…
- you need cheap coding tiers
- you need bulk generation
- you need experiments where data residency is not a constraint
The reason a thousand people argued on Hacker News this week: frontier-adjacent coding for pocket change, with the caveats you would expect.
Caveats: Open-weights status and licence not verified from a primary source at time of writing. Off-peak and peak pricing differ; the cheap numbers are off-peak. Data handling terms should be read before any enterprise use.
What practitioners say
Claude Opus 5.5: The launch thread was the biggest Claude thread of the year on Hacker News, a port of the TypeScript compiler to Rust credited the model with a working build in ten hours, and a Vals AI materials-discovery run used it for agentic simulation. A 'has it been nerfed yet' tracker is the most-upvoted scepticism.
DeepSeek Flash (4.1): The 'why isn't the industry freaking out' post hit 1,067 points; the most-upvoted replies say the price is real and the coding gap to Opus is also real.
Questions people ask
Which is better, Claude Opus 5.5 or DeepSeek Flash (4.1)?
Claude Opus 5.5 scores higher on the Models at Work leaderboard (91 vs 70 out of 100). DeepSeek Flash (4.1) is about 15× cheaper per blended million tokens ($0.52 vs $8).
When should I choose Claude Opus 5.5 over DeepSeek Flash (4.1)?
Choose Claude Opus 5.5 for agentic coding, long-running agents, enterprise knowledge work. The model people actually ship agents on: top of the independent index, a price that does not need a budget meeting, and a community that complains mainly about how much it has to be used.
When should I choose DeepSeek Flash (4.1) over Claude Opus 5.5?
Choose DeepSeek Flash (4.1) for cheap coding tiers, bulk generation, experiments where data residency is not a constraint. The reason a thousand people argued on Hacker News this week: frontier-adjacent coding for pocket change, with the caveats you would expect.
Which is cheaper, Claude Opus 5.5 or DeepSeek Flash (4.1)?
Claude Opus 5.5 costs $4 per million input tokens and $20 per million output tokens on Anthropic's list price (Claude pricing, read Oct 10, 2026). DeepSeek Flash (4.1) costs $0.30 per million input tokens and $1.20 per million output tokens on DeepSeek's list price (DeepSeek API pricing, read Oct 10, 2026).
Scores come from the Models at Work leaderboard: Score is 0 to 100: 50% independent evals normalised within this table, 20% price-performance, 15% practitioner sentiment from Signals and community threads, 15% operational fit (context, speed, availability, open weights). Models within three points are a tie in practice. Vendor-published figures are labelled as such and never counted as independent. Prices are vendor list prices where published; blended figures assume three input tokens per output token.