Compare / Claude Sonnet 5.5 vs DeepSeek-V4.1-Flash-1017
Claude Sonnet 5.5 vs DeepSeek-V4.1-Flash-1017
Which is cheaper, which is more capable, and which does better at each kind of work, from 64 results on 4 sources that measured both models.
Of the 64 results both models have, the better value on each. Results whose reported ranges overlap are too close to call.
Results as of 20 October 2026 (catalogue release 2026-10-20-96eb40c3ec63). See also Anthropic vs DeepSeek, every model from both labs.
Claude Sonnet 5.5 or DeepSeek-V4.1-Flash-1017? The short answer
Pick Claude Sonnet 5.5 if quality matters most: it scores higher (Spring Prompt overall 63 against 44). Pick DeepSeek-V4.1-Flash-1017 if cost matters more: it costs 11 times less per product listing on CatalogBench. DeepSeek-V4.1-Flash-1017 is also faster.
- Spring Prompt overall: Claude Sonnet 5.5 63, DeepSeek-V4.1-Flash-1017 44 (out of 100; how the score works).
- DeepSeek-V4.1-Flash-1017 is cheaper to run: $0.002 against $0.017 per product listing on CatalogBench (11 times less).
- Claude Sonnet 5.5 scores higher on the Artificial Analysis Intelligence Index: 56.0 against 45.1.
- DeepSeek-V4.1-Flash-1017 writes faster: 212 tokens a second against 137.
- DeepSeek-V4.1-Flash-1017 is newer: released 17 Oct 2026, against 28 Sep 2026 for Claude Sonnet 5.5.
- On our own benchmarks, on the results both models have: Claude Sonnet 5.5 does better for product listings, decks from an analysis and marketing planning.
- On third-party benchmarks, on the results both models have: Claude Sonnet 5.5 does better for agents and tool use and reasoning and knowledge.
Head to head
Every fact side by side
| Claude Sonnet 5.5 | DeepSeek-V4.1-Flash-1017 | |
|---|---|---|
| Price per million tokens | $2.00 in · $10.00 out | $0.30 in · $1.20 out |
| Blended (3 in : 1 out) | $4.00 | $0.52 |
| Cheapest host, blended | $4.00 (Amazon Bedrock) | – |
| Cost per product listing (CatalogBench) | $0.017 | $0.002 |
| Cached input, per million | $0.20 cached input | $0.006 cached input |
| Intelligence Index | 56.0 | 45.1 |
| Spring Prompt overall | 63 | 44 |
| Output speed, tokens a second | 137 | 212 |
| Context window | 1,000,000 tokens | 1,048,576 tokens |
| Released | 28 Sep 2026 | 17 Oct 2026 (newer) |
| Weights | Closed | Open |
| Developer based in | the US | China |
Prices are the developer's list price where we have read it, otherwise the typical host on OpenRouter; see every model's price. Intelligence and speed from Artificial Analysis.
Which is better for what
Each model's rank among the models on sale today, for each kind of work, from our own benchmarks and licensed sources. Further right is better; the better rank is in green.
From our research
- Claude Haiku 5.5 Is Far Better Than Haiku 4.5 at a Tenth of the Price. GPT-6 Luna Still Beats It at Business Work. 8 Oct 2026
- DeepSeek-V4.1-Flash-1017 review: better at analysis, much worse at sticking to the product data 19 Oct 2026
- Mercury 3 first look: very fast with thinking off, too slow with it on 20 Oct 2026
- MiniMax M3.1 Flash first look: careful with product data, unreliable on long jobs 19 Oct 2026
Every shared result
Each model's best result on every measure both have, grouped by benchmark, with the setting that produced it. Under each measure, every model that benchmark has measured is a grey tick, best to the right, so you can see where the two sit in the field. The headline measures of each benchmark come first; the rest are under "Show all". Green marks the better value; where a source reports ranges that overlap, neither is marked.
| Measure | Claude Sonnet 5.5 | DeepSeek-V4.1-Flash-1017 |
|---|---|---|
| CatalogBench measured by Spring Prompt · 3 results | ||
| Cost per productUS dollars, lower is better 16 · 4 of 24 measured | $0.0172 | $0.0015 |
| Reliably publish-ready% of products, higher is better 15 · 19 of 24 measured | 32.1% | 21.4% |
| Reliably publish-ready · sales brief% of products, higher is better 12 · 21 of 24 measured | 10.7% | 0.0% |
| DeckBench measured by Spring Prompt · 3 results | ||
| Cost per deckUS dollars, lower is better 16 · 7 of 24 measured | $0.15 | $0.0255 |
| Deck ratingrating, higher is betterThe rating weighs each win by how strong the other deck was; the win rate counts wins against whichever decks a model happened to meet, so the two can disagree. 5 · 12 of 24 measured | 1,408 | 1,145 |
| Accurate decks% of tasks, higher is better 6 · 14 of 24 measured | 66.7% | 33.3% |
| ROASBench measured by Spring Prompt · 3 results | ||
| Overall scorescore out of 100, higher is better 4 · 11 of 24 measured | 52.0 | 41.4 |
| Audience scorescore out of 100, higher is better 11 · 9 of 24 measured | 61.8 | 65.3 |
| Business scorescore out of 100, higher is better 2 · 11 of 24 measured | 57.2 | 38.3 |
| Artificial Analysis reported by Artificial Analysis · 3 results | ||
| Artificial Analysis Intelligence Indexindex score, higher is better 2 · 16 of 249 measured | 56.0max reasoning | 45.1max reasoning |
| Humanity's Last Exam% of questions, higher is better 5 · 27 of 248 measured | 55.0%max reasoning | 43.3%max reasoning |
| Terminal-Bench 4.0% of tasks, higher is better 1 · 16 of 118 measured | 63.6%max reasoning | 33.8%max reasoning |
Show all 64 results (52 more)
| Measure | Claude Sonnet 5.5 | DeepSeek-V4.1-Flash-1017 |
|---|---|---|
| CatalogBench measured by Spring Prompt · 28 results | ||
| Channel compliance% of products, higher is better 17 · 1 of 24 measured | 99.4% | 100.0% |
| Channel rules broken% of products, lower is better 19 · 19 of 24 measured | 1.2% | 1.2% |
| Channel rules broken · sales brief% of products, lower is better 12 · 22 of 24 measured | 0.6% | 2.4% |
| Claims to check% of products, lower is better 1 · 19 of 24 measured | 0.0% | 1.2% |
| Claims to check · sales brief% of products, lower is better 14 · 18 of 24 measured | 0.6% | 3.6% |
| Conflicts caught% of conflicts, higher is better 1 · 1 of 24 measured | 100.0% | 100.0% |
| Content quality% of checks, higher is better 15 · 20 of 24 measured | 96.5% | 95.3% |
| Content quality · sales brief% of checks, higher is better 11 · 19 of 24 measured | 97.3% | 94.8% |
| Decision accuracy% of decisions, higher is better 15 · 18 of 24 measured | 95.7% | 94.9% |
| Failed outputs% of products, lower is better 1 · 1 of 24 measured | 0.0% | 0.0% |
| Failed outputs · sales brief% of products, lower is better 1 · 1 of 24 measured | 0.0% | 0.0% |
| Field accuracy% of missing fields, higher is better 21 · 10 of 24 measured | 91.5% | 93.7% |
| Invented values% of filled values, lower is better 7 · 13 of 24 measured | 0.8% | 1.7% |
| Missing UK information% of products, lower is better 1 · 1 of 24 measured | 0.0% | 0.0% |
| Missing UK information · sales brief% of products, lower is better 1 · 1 of 24 measured | 0.0% | 0.0% |
| Not findable% of products, lower is better 1 · 5 of 24 measured | 1.2% | 3.6% |
| Not findable · sales brief% of products, lower is better 1 · 7 of 24 measured | 0.6% | 2.4% |
| Publish-ready listings% of products, higher is better 17 · 19 of 24 measured | 46.4% | 40.5% |
| Publish-ready listings · sales brief% of products, higher is better 13 · 21 of 24 measured | 27.4% | 8.3% |
| Time per productseconds, lower is better 8 · 3 of 24 measured | 9.90 | 6.70 |
| Unsupported claimsclaims per product, lower is better 17 · 21 of 24 measured | 1.08 | 1.70 |
| Unsupported claims% of products, lower is better 19 · 20 of 24 measured | 39.3% | 44.6% |
| Unsupported claims · sales briefclaims per product, lower is better 12 · 22 of 24 measured | 1.71 | 4.01 |
| Unsupported claims · sales brief% of products, lower is better 11 · 23 of 24 measured | 59.5% | 85.7% |
| Wrong attributes% of products, lower is better 15 · 13 of 24 measured | 19.1% | 17.9% |
| Wrong attributes · sales brief% of products, lower is better 18 · 21 of 24 measured | 20.8% | 22.0% |
| Wrong category or variant% of products, lower is better 15 · 2 of 24 measured | 3.0% | 0.6% |
| Wrong category or variant · sales brief% of products, lower is better 16 · 3 of 24 measured | 3.0% | 1.2% |
| DeckBench measured by Spring Prompt · 14 results | ||
| Caveat dropped% of tasks, lower is better 12 · 12 of 24 measured | 16.7% | 16.7% |
| Clean layout% of tasks, higher is better 1 · 20 of 24 measured | 100.0% | 16.7% |
| Design quality% of the maximum, higher is better 4 · 9 of 24 measured | 78.5% | 68.5% |
| Draft figure quoted% of tasks, lower is better 1 · 19 of 24 measured | 0.0% | 50.0% |
| Findings missing% of tasks, lower is better 1 · 1 of 24 measured | 0.0% | 0.0% |
| Head-to-head win rate% of comparisons, higher is betterThe rating weighs each win by how strong the other deck was; the win rate counts wins against whichever decks a model happened to meet, so the two can disagree. 4 · 14 of 24 measured | 85.6% | 53.3% |
| Layout defects% of tasks, lower is better 1 · 20 of 24 measured | 0.0% | 83.3% |
| Misleading metric used% of tasks, lower is better 1 · 1 of 24 measured | 0.0% | 0.0% |
| Presentable decks% of tasks, higher is better 2 · 12 of 24 measured | 50.0% | 0.0% |
| Recommendation late or wrong% of tasks, lower is better 9 · 9 of 24 measured | 16.7% | 16.7% |
| Slides needing work% of tasks, lower is better 7 · 16 of 24 measured | 33.3% | 66.7% |
| Time per deckseconds, lower is better 10 · 7 of 24 measured | 83.4 | 73.0 |
| Unsupported claims% of tasks, lower is better 1 · 11 of 24 measured | 0.0% | 16.7% |
| Unsupported numbers% of tasks, lower is better 1 · 1 of 24 measured | 0.0% | 0.0% |
| ROASBench measured by Spring Prompt · 6 results | ||
| Consistency scorescore out of 100, higher is better 10 · 15 of 24 measured | 28.5 | 20.2 |
| Contribution profitsimulated US dollars, higher is better 11 · 10 of 24 measured | $571,203 | $585,572 |
| Cost of a runUS dollars, lower is better 16 · 8 of 24 measured | $0.42 | $0.0799 |
| Months over budgetmonths of 12, lower is better 1 · 1 of 24 measured | 0 | 0 |
| Planning scorescore out of 100, higher is better 3 · 20 of 24 measured | 55.1 | 54.3 |
| Return on ad spendprofit per $1 spent, higher is better 1 · 12 of 24 measured | $0.70 | $0.44 |
| Artificial Analysis reported by Artificial Analysis · 4 results | ||
| Long-context reasoning (AA-LCR)% of questions, higher is better 19 · 19 of 239 measured | 82.7%max reasoning | 82.7%max reasoning |
| Output speedtokens per second, higher is better 33 · 15 of 78 measured | 137max reasoning | 212max reasoning |
| SciCode% of problems, higher is better 4 · 24 of 119 measured | 61.0%max reasoning | 55.9%max reasoning |
| Time to first answer tokenseconds, lower is better 17 · 46 of 78 measured | 0.71low reasoning | 10.5max reasoning |
Compare them with other models
- Anthropic vs DeepSeekEvery model from both labs, best against best
- Claude Sonnet 5.5 vs Claude Opus 5.5Most intelligent at $3–10 per million tokens
- Claude Sonnet 5.5 vs Muse WonderFastest with similar intelligence
- Claude Sonnet 5.5 vs Claude Fable 5.1Just above overall
- Claude Sonnet 5.5 vs Muse Spark 1.3Just below overall
- DeepSeek-V4.1-Flash-1017 vs Claude Haiku 5.5Cheapest with similar intelligence
- DeepSeek-V4.1-Flash-1017 vs Muse Spark 1.3Fastest with similar intelligence
- DeepSeek-V4.1-Flash-1017 vs Claude Opus 5.5Most intelligent available today
Quick answers
Is Claude Sonnet 5.5 better than DeepSeek-V4.1-Flash-1017?
Pick Claude Sonnet 5.5 if quality matters most: it scores higher (Spring Prompt overall 63 against 44). Pick DeepSeek-V4.1-Flash-1017 if cost matters more: it costs 11 times less per product listing on CatalogBench. DeepSeek-V4.1-Flash-1017 is also faster.
Which is cheaper, Claude Sonnet 5.5 or DeepSeek-V4.1-Flash-1017?
DeepSeek-V4.1-Flash-1017 is cheaper to run: $0.002 against $0.017 per product listing on CatalogBench (11 times less).
Which is faster, Claude Sonnet 5.5 or DeepSeek-V4.1-Flash-1017?
DeepSeek-V4.1-Flash-1017 writes about 212 tokens a second on its usual API, against 137 for Claude Sonnet 5.5 (Artificial Analysis).
Which is better for product listings, Claude Sonnet 5.5 or DeepSeek-V4.1-Flash-1017?
Claude Sonnet 5.5 ranks 13 of 24 models on sale for turning a sparse product feed and photos into listings that can go live, against 21 for DeepSeek-V4.1-Flash-1017.
Which is better for decks from an analysis, Claude Sonnet 5.5 or DeepSeek-V4.1-Flash-1017?
Claude Sonnet 5.5 ranks 5 of 24 models on sale for turning a finished analysis into a deck you could present as it is, against 12 for DeepSeek-V4.1-Flash-1017.
Which is better for marketing planning, Claude Sonnet 5.5 or DeepSeek-V4.1-Flash-1017?
Claude Sonnet 5.5 ranks 4 of 24 models on sale for planning a year of ad spend without overspending, against 11 for DeepSeek-V4.1-Flash-1017.
Which is better for agents and tool use, Claude Sonnet 5.5 or DeepSeek-V4.1-Flash-1017?
Claude Sonnet 5.5 ranks 1 of 168 models on sale for multi-step tasks with tools: support desks, coding agents, function calls, against 22 for DeepSeek-V4.1-Flash-1017.
Which has the bigger context window, Claude Sonnet 5.5 or DeepSeek-V4.1-Flash-1017?
DeepSeek-V4.1-Flash-1017: 1,048,576 tokens, against 1,000,000 for Claude Sonnet 5.5.
Run Claude Sonnet 5.5 and DeepSeek-V4.1-Flash-1017 on your own prompt
Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.