Compare / DeepSeek-V4-Pro (0423) vs Particle-1
DeepSeek-V4-Pro (0423) vs Particle-1
Which is cheaper, which is more capable, and which does better at each kind of work, from 26 results on 2 sources that measured both models.
Of the 26 results both models have, the better value on each. Results whose reported ranges overlap are too close to call.
Results as of 10 November 2026 (catalogue release 2026-11-10-8342a7178929).
DeepSeek-V4-Pro (0423) or Particle-1? The short answer
They score about the same, so pick Particle-1: it costs 5.4 times less per deck on DeckBench.
- Spring Prompt overall: DeepSeek-V4-Pro (0423) 28, Particle-1 31 (out of 100; how the score works).
- Particle-1 is cheaper to run: $0.009 against $0.046 per deck on DeckBench (5.4 times less).
- On our own benchmarks, on the results both models have: Particle-1 does better for decks from an analysis and marketing planning.
Head to head
Every fact side by side
| DeepSeek-V4-Pro (0423) | Particle-1 | |
|---|---|---|
| Price per million tokens | $1.42 in · $2.83 out | $0.050 in · $0.50 out |
| Blended (3 in : 1 out) | $1.77 | $0.16 |
| Cheapest host, blended | $1.05 (Relace, FP4) | – |
| Cost per deck (DeckBench) | $0.046 | $0.009 |
| Intelligence Index | 30.4 | – |
| Spring Prompt overall | 28 | 31 |
| Output speed, tokens a second | – | – |
| Context window | 1,048,576 tokens | 1,048,576 tokens |
| Released | 24 Apr 2026 | – |
| Weights | Open | Closed |
| Developer based in | 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.
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-Pro (0423) | Particle-1 |
|---|---|---|
| DeckBench measured by Spring Prompt · 3 results | ||
| Cost per deckUS dollars, lower is better 14 · 2 of 30 measured | $0.0465 | $0.0086 |
| 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. 30 · 17 of 30 measured | 560 | 1,143 |
| Accurate decks% of tasks, higher is better 25 · 21 of 30 measured | 0.0% | 16.7% |
| ROASBench measured by Spring Prompt · 3 results | ||
| Overall scorescore out of 100, higher is better 23 · 16 of 30 measured | 28.3 | 43.3 |
| Audience scorescore out of 100, higher is better 26 · 14 of 30 measured | 44.8 | 65.1 |
| Business scorescore out of 100, higher is better 23 · 15 of 30 measured | 23.8 | 39.0 |
Show all 26 results (20 more)
| Measure | DeepSeek-V4-Pro (0423) | Particle-1 |
|---|---|---|
| DeckBench measured by Spring Prompt · 14 results | ||
| Caveat dropped% of tasks, lower is better 14 · 1 of 30 measured | 16.7% | 0.0% |
| Clean layout% of tasks, higher is better 16 · 23 of 30 measured | 33.3% | 16.7% |
| Design quality% of the maximum, higher is better 28 · 24 of 30 measured | 40.9% | 54.4% |
| Draft figure quoted% of tasks, lower is better 17 · 23 of 30 measured | 33.3% | 50.0% |
| Findings missing% of tasks, lower is better 20 · 1 of 30 measured | 16.7% | 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. 30 · 18 of 30 measured | 24.4% | 50.0% |
| Layout defects% of tasks, lower is better 16 · 23 of 30 measured | 66.7% | 83.3% |
| Misleading metric used% of tasks, lower is better 1 · 1 of 30 measured | 0.0% | 0.0% |
| Presentable decks% of tasks, higher is better 14 · 14 of 30 measured | 0.0% | 0.0% |
| Recommendation late or wrong% of tasks, lower is better 25 · 17 of 30 measured | 66.7% | 33.3% |
| Slides needing work% of tasks, lower is better 28 · 9 of 30 measured | 83.3% | 33.3% |
| Time per deckseconds, lower is better 26 · 18 of 30 measured | 332 | 154 |
| Unsupported claims% of tasks, lower is better 29 · 1 of 30 measured | 66.7% | 0.0% |
| Unsupported numbers% of tasks, lower is better 1 · 1 of 30 measured | 0.0% | 0.0% |
| ROASBench measured by Spring Prompt · 6 results | ||
| Consistency scorescore out of 100, higher is better 28 · 17 of 30 measured | 9.1 | 27.8 |
| Contribution profitsimulated US dollars, higher is better 22 · 10 of 30 measured | $301,289 | $684,624 |
| Cost of a runUS dollars, lower is better 17 · 3 of 30 measured | $0.20 | $0.0234 |
| Months over budgetmonths of 12, lower is better 1 · 1 of 30 measured | 0 | 0 |
| Planning scorescore out of 100, higher is better 28 · 26 of 30 measured | 54.0 | 54.3 |
| Return on ad spendprofit per $1 spent, higher is better 22 · 15 of 30 measured | $0.26 | $0.51 |
Compare them with other models
- DeepSeek-V4-Pro (0423) vs Muse Spark 1.3Most intelligent at $1–3 per million tokens
- DeepSeek-V4-Pro (0423) vs Claude Opus 5.5Most intelligent available today
- Particle-1 vs Muse EmberHighest-scoring overall at under $0.25 per million tokens
- Particle-1 vs Claude Fable 5.2Highest-scoring overall available today
- Particle-1 vs GLM-5.3 FlashX LegalJust above overall
Quick answers
Is DeepSeek-V4-Pro (0423) better than Particle-1?
They score about the same, so pick Particle-1: it costs 5.4 times less per deck on DeckBench.
Which is cheaper, DeepSeek-V4-Pro (0423) or Particle-1?
Particle-1 is cheaper to run: $0.009 against $0.046 per deck on DeckBench (5.4 times less).
Which is better for decks from an analysis, DeepSeek-V4-Pro (0423) or Particle-1?
Particle-1 ranks 17 of 29 models on sale for turning a finished analysis into a deck you could present as it is, against 29 for DeepSeek-V4-Pro (0423).
Which is better for marketing planning, DeepSeek-V4-Pro (0423) or Particle-1?
Particle-1 ranks 16 of 29 models on sale for planning a year of ad spend without overspending, against 23 for DeepSeek-V4-Pro (0423).
Run DeepSeek-V4-Pro (0423) and Particle-1 on your own prompt.
Benchmarks aren't your task. Test both side by side on your prompt, with every answer checked against your rules and the cost of each one.