Compare / DeepSeek-V4.1-Flash-1017 vs MiniMax M3.1 Flash
DeepSeek-V4.1-Flash-1017 vs MiniMax M3.1 Flash
Which is cheaper, which is more capable, and which does better at each kind of work, from 84 results on 5 sources that measured both models.
Of the 84 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 DeepSeek vs MiniMax, every model from both labs.
DeepSeek-V4.1-Flash-1017 or MiniMax M3.1 Flash? The short answer
They score about the same, so pick MiniMax M3.1 Flash: it costs 2.0 times less per token.
- Spring Prompt overall: DeepSeek-V4.1-Flash-1017 44, MiniMax M3.1 Flash 47 (out of 100; how the score works).
- MiniMax M3.1 Flash is cheaper: $0.26 against $0.52 per million tokens, 2.0 times less.
- DeepSeek-V4.1-Flash-1017 scores higher on the Artificial Analysis Intelligence Index: 45.1 against 42.4.
- MiniMax M3.1 Flash is newer: released 19 Oct 2026, against 17 Oct 2026 for DeepSeek-V4.1-Flash-1017.
- On our own benchmarks, on the results both models have: DeepSeek-V4.1-Flash-1017 does better for user surveys and marketing planning; MiniMax M3.1 Flash for product listings.
- On third-party benchmarks, on the results both models have: DeepSeek-V4.1-Flash-1017 does better for agents and tool use.
Head to head
Every fact side by side
| DeepSeek-V4.1-Flash-1017 | MiniMax M3.1 Flash | |
|---|---|---|
| Price per million tokens | $0.30 in · $1.20 out | $0.15 in · $0.60 out |
| Blended (3 in : 1 out) | $0.52 | $0.26 |
| Cheapest host, blended | – | – |
| Cached input, per million | $0.006 cached input | $0.015 cached input |
| Intelligence Index | 45.1 | 42.4 |
| Spring Prompt overall | 44 | 47 |
| Output speed, tokens a second | 212 | 159 |
| Context window | 1,048,576 tokens | 1,048,576 tokens |
| Released | 17 Oct 2026 | 19 Oct 2026 (newer) |
| Weights | Open | Closed |
| Developer based in | China | 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
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 | DeepSeek-V4.1-Flash-1017 | MiniMax M3.1 Flash |
|---|---|---|
| CatalogBench measured by Spring Prompt · 3 results | ||
| Cost per productUS dollars, lower is better 4 · 1 of 24 measured | $0.0015 | $0 |
| Reliably publish-ready% of products, higher is better 19 · 9 of 24 measured | 21.4% | 50.0% |
| Reliably publish-ready · sales brief% of products, higher is better 21 · 6 of 24 measured | 0.0% | 37.5% |
| DeckBench measured by Spring Prompt · 3 results | ||
| Cost per deckUS dollars, lower is better 7 · 1 of 24 measured | $0.0255 | $0 |
| 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. 12 · 14 of 24 measured | 1,145 | 1,090 |
| Accurate decks% of tasks, higher is better 14 · 9 of 24 measured | 33.3% | 50.0% |
| ROASBench measured by Spring Prompt · 3 results | ||
| Overall scorescore out of 100, higher is better 11 · 12 of 24 measured | 41.4 | 40.3 |
| Audience scorescore out of 100, higher is better 9 · 12 of 24 measured | 65.3 | 60.8 |
| Business scorescore out of 100, higher is better 11 · 10 of 24 measured | 38.3 | 38.9 |
| SurveyBench measured by Spring Prompt · 3 results | ||
| Analysis ratingrating, higher is betterThe rating weighs each win by how strong the other analysis was; the win rate counts wins against whichever analyses a model happened to meet, so the two can disagree. 5 · 13 of 13 measured | 1,221 | 441 |
| Analysis scorepoints of 100, higher is better 4 · 13 of 13 measured | 90.2 | 7.90 |
| Head-to-head win rate% of comparisons, higher is betterThe rating weighs each win by how strong the other analysis was; the win rate counts wins against whichever analyses a model happened to meet, so the two can disagree. 5 · 13 of 13 measured | 60.2% | 15.9% |
| Artificial Analysis reported by Artificial Analysis · 3 results | ||
| Artificial Analysis Intelligence Indexindex score, higher is better 16 · 21 of 249 measured | 45.1max reasoning | 42.4 |
| Humanity's Last Exam% of questions, higher is better 27 · 14 of 248 measured | 43.3%max reasoning | 48.0% |
| Terminal-Bench 4.0% of tasks, higher is better 16 · 22 of 118 measured | 33.8%max reasoning | 25.8% |
Show all 84 results (69 more)
| Measure | DeepSeek-V4.1-Flash-1017 | MiniMax M3.1 Flash |
|---|---|---|
| CatalogBench measured by Spring Prompt · 29 results | ||
| Channel compliance% of products, higher is better 1 · 1 of 24 measured | 100.0% | 100.0% |
| Channel rules broken% of products, lower is better 19 · 12 of 24 measured | 1.2% | 0.6% |
| Channel rules broken · sales brief% of products, lower is better 22 · 1 of 24 measured | 2.4% | 0.0% |
| Claims to check% of products, lower is better 19 · 1 of 24 measured | 1.2% | 0.0% |
| Claims to check · sales brief% of products, lower is better 18 · 1 of 24 measured | 3.6% | 0.0% |
| Conflicts caught% of conflicts, higher is better 1 · 1 of 24 measured | 100.0% | 100.0% |
| Content quality% of checks, higher is better 20 · 17 of 24 measured | 95.3% | 95.8% |
| Content quality · sales brief% of checks, higher is better 19 · 17 of 24 measured | 94.8% | 96.0% |
| Decision accuracy% of decisions, higher is better 18 · 16 of 24 measured | 94.9% | 95.6% |
| Failed outputs% of products, lower is better 1 · 22 of 24 measured | 0.0% | 1.8% |
| Failed outputs · sales brief% of products, lower is better 1 · 22 of 24 measured | 0.0% | 1.8% |
| Field accuracy% of missing fields, higher is better 10 · 19 of 24 measured | 93.7% | 92.0% |
| Invented values% of filled values, lower is better 13 · 22 of 24 measured | 1.7% | 3.8% |
| 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 5 · 16 of 24 measured | 3.6% | 7.1% |
| Not findable · sales brief% of products, lower is better 7 · 12 of 24 measured | 2.4% | 4.2% |
| Output tokens per producttokens, lower is better | 1,226 | 2,890 |
| Publish-ready listings% of products, higher is better 19 · 11 of 24 measured | 40.5% | 63.1% |
| Publish-ready listings · sales brief% of products, higher is better 21 · 7 of 24 measured | 8.3% | 57.1% |
| Time per productseconds, lower is better 3 · 19 of 24 measured | 6.70 | 32.0 |
| Unsupported claimsclaims per product, lower is better 21 · 6 of 24 measured | 1.70 | 0.39 |
| Unsupported claims% of products, lower is better 20 · 5 of 24 measured | 44.6% | 7.7% |
| Unsupported claims · sales briefclaims per product, lower is better 22 · 6 of 24 measured | 4.01 | 0.60 |
| Unsupported claims · sales brief% of products, lower is better 23 · 5 of 24 measured | 85.7% | 16.1% |
| Wrong attributes% of products, lower is better 13 · 20 of 24 measured | 17.9% | 22.6% |
| Wrong attributes · sales brief% of products, lower is better 21 · 20 of 24 measured | 22.0% | 21.4% |
| Wrong category or variant% of products, lower is better 2 · 20 of 24 measured | 0.6% | 4.2% |
| Wrong category or variant · sales brief% of products, lower is better 3 · 21 of 24 measured | 1.2% | 4.8% |
| DeckBench measured by Spring Prompt · 15 results | ||
| Caveat dropped% of tasks, lower is better 12 · 24 of 24 measured | 16.7% | 33.3% |
| Clean layout% of tasks, higher is better 20 · 23 of 24 measured | 16.7% | 0.0% |
| Design quality% of the maximum, higher is better 9 · 21 of 24 measured | 68.5% | 46.2% |
| Draft figure quoted% of tasks, lower is better 19 · 12 of 24 measured | 50.0% | 33.3% |
| Findings missing% of tasks, lower is better 1 · 24 of 24 measured | 0.0% | 50.0% |
| 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. 14 · 15 of 24 measured | 53.3% | 48.6% |
| Layout defects% of tasks, lower is better 20 · 23 of 24 measured | 83.3% | 100.0% |
| Misleading metric used% of tasks, lower is better 1 · 24 of 24 measured | 0.0% | 33.3% |
| Output tokens per decktokens, lower is better 1 · 3 of 3 measured | 21,019 | 45,141 |
| Presentable decks% of tasks, higher is better 12 · 12 of 24 measured | 0.0% | 0.0% |
| Recommendation late or wrong% of tasks, lower is better 9 · 13 of 24 measured | 16.7% | 33.3% |
| Slides needing work% of tasks, lower is better 16 · 21 of 24 measured | 66.7% | 83.3% |
| Time per deckseconds, lower is better 7 · 20 of 24 measured | 73.0 | 330 |
| Unsupported claims% of tasks, lower is better 11 · 21 of 24 measured | 16.7% | 50.0% |
| Unsupported numbers% of tasks, lower is better 1 · 24 of 24 measured | 0.0% | 50.0% |
| ROASBench measured by Spring Prompt · 6 results | ||
| Consistency scorescore out of 100, higher is better 15 · 17 of 24 measured | 20.2 | 17.3 |
| Contribution profitsimulated US dollars, higher is better 10 · 5 of 24 measured | $585,572 | $693,379 |
| Cost of a runUS dollars, lower is better 8 · 1 of 24 measured | $0.0799 | $0 |
| Months over budgetmonths of 12, lower is better 1 · 1 of 24 measured | 0 | 0 |
| Planning scorescore out of 100, higher is better 20 · 21 of 24 measured | 54.3 | 54.2 |
| Return on ad spendprofit per $1 spent, higher is better 12 · 9 of 24 measured | $0.44 | $0.52 |
| SurveyBench measured by Spring Prompt · 15 results | ||
| Leading or double-barrelled questions% of tasks, lower is better 3 · 12 of 13 measured | 11.1% | 77.8% |
| Mistaken next steps% of tasks, lower is better 1 · 13 of 13 measured | 0.0% | 100.0% |
| Numbers right% of answers, higher is better 1 · 1 of 13 measured | 100.0% | 100.0% |
| Objectives unanswerable% of tasks, lower is better 7 · 13 of 13 measured | 11.1% | 66.7% |
| Precision ignored% of tasks, lower is better 1 · 10 of 13 measured | 0.0% | 66.7% |
| Research scorepoints of 100, higher is better 4 · 13 of 13 measured | 90.9 | 16.4 |
| Sound research% of tasks, higher is better 3 · 6 of 13 measured | 33.3% | 0.0% |
| Stakeholder's view presumed% of tasks, lower is better 1 · 12 of 13 measured | 0.0% | 55.6% |
| Survey plan scorepoints of 100, higher is better 4 · 13 of 13 measured | 92.5 | 36.1 |
| Survey structure% of tasks, lower is better 10 · 13 of 13 measured | 33.3% | 77.8% |
| Traps handled% of traps, higher is better 5 · 8 of 13 measured | 91.3% | 75.0% |
| Traps missed% of tasks, lower is better 5 · 10 of 13 measured | 44.4% | 100.0% |
| Unsupported findings% of tasks, lower is better 4 · 10 of 13 measured | 44.4% | 100.0% |
| Wrong numbers% of tasks, lower is better 1 · 10 of 13 measured | 0.0% | 88.9% |
| Wrong recommendation% of tasks, lower is better 3 · 13 of 13 measured | 11.1% | 100.0% |
| Artificial Analysis reported by Artificial Analysis · 4 results | ||
| Long-context reasoning (AA-LCR)% of questions, higher is better 19 · 45 of 239 measured | 82.7%max reasoning | 79.7% |
| Output speedtokens per second, higher is better 15 · 21 of 78 measured | 212max reasoning | 159 |
| SciCode% of problems, higher is better 24 · 36 of 119 measured | 55.9%max reasoning | 53.4% |
| Time to first answer tokenseconds, lower is better 46 · 51 of 78 measured | 10.5max reasoning | 13.3 |
Compare them with other models
- DeepSeek vs MiniMaxEvery model from both labs, best against best
- 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
- MiniMax M3.1 Flash vs Claude Haiku 5.5Cheapest with similar intelligence
- MiniMax M3.1 Flash vs DeepSeek-V4.1-FlashFastest with similar intelligence
- MiniMax M3.1 Flash vs Claude Opus 5.5Most intelligent available today
Quick answers
Is DeepSeek-V4.1-Flash-1017 better than MiniMax M3.1 Flash?
They score about the same, so pick MiniMax M3.1 Flash: it costs 2.0 times less per token.
Which is cheaper, DeepSeek-V4.1-Flash-1017 or MiniMax M3.1 Flash?
MiniMax M3.1 Flash is cheaper: $0.26 against $0.52 per million tokens, 2.0 times less.
Which is faster, DeepSeek-V4.1-Flash-1017 or MiniMax M3.1 Flash?
DeepSeek-V4.1-Flash-1017 writes about 212 tokens a second on its usual API, against 159 for MiniMax M3.1 Flash (Artificial Analysis).
Which is better for product listings, DeepSeek-V4.1-Flash-1017 or MiniMax M3.1 Flash?
MiniMax M3.1 Flash ranks 7 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, DeepSeek-V4.1-Flash-1017 or MiniMax M3.1 Flash?
DeepSeek-V4.1-Flash-1017 ranks 12 of 24 models on sale for turning a finished analysis into a deck you could present as it is, against 14 for MiniMax M3.1 Flash.
Which is better for user surveys, DeepSeek-V4.1-Flash-1017 or MiniMax M3.1 Flash?
DeepSeek-V4.1-Flash-1017 ranks 5 of 13 models on sale for planning a user survey and reading its results without being misled, against 13 for MiniMax M3.1 Flash.
Which is better for marketing planning, DeepSeek-V4.1-Flash-1017 or MiniMax M3.1 Flash?
DeepSeek-V4.1-Flash-1017 ranks 11 of 24 models on sale for planning a year of ad spend without overspending, against 12 for MiniMax M3.1 Flash.
Run DeepSeek-V4.1-Flash-1017 and MiniMax M3.1 Flash on your own prompt
Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.