Compare / DeepSeek-V4-Pro (0423) vs Mercury 3
DeepSeek-V4-Pro (0423) vs Mercury 3
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 20 October 2026 (catalogue release 2026-10-20-96eb40c3ec63).
DeepSeek-V4-Pro (0423) or Mercury 3? The short answer
Pick Mercury 3: it scores higher (Spring Prompt overall 39 against 31) and costs less.
- Spring Prompt overall: DeepSeek-V4-Pro (0423) 31, Mercury 3 39 (out of 100; how the score works).
- Mercury 3 is cheaper to run: $0.012 against $0.046 per deck on DeckBench (4.0 times less).
- Mercury 3 is newer: released 19 Oct 2026, against 24 Apr 2026 for DeepSeek-V4-Pro (0423).
- On our own benchmarks, on the results both models have: DeepSeek-V4-Pro (0423) does better for marketing planning; Mercury 3 for decks from an analysis.
Head to head
Every fact side by side
| DeepSeek-V4-Pro (0423) | Mercury 3 | |
|---|---|---|
| Price per million tokens | $1.42 in · $2.83 out | $0.20 in · $0.70 out |
| Blended (3 in : 1 out) | $1.77 | $0.33 |
| Cheapest host, blended | $1.19 (StreamLake, FP8) | – |
| Cost per deck (DeckBench) | $0.046 | $0.012 |
| Cached input, per million | – | $0.020 cached input |
| Intelligence Index | 30.4 | – |
| Spring Prompt overall | 31 | 39 |
| Output speed, tokens a second | – | – |
| Context window | 1,048,576 tokens | 1,000,000 tokens |
| Released | 24 Apr 2026 | 19 Oct 2026 (newer) |
| Weights | Open | Closed |
| Developer based in | China | the US |
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-Pro (0423) | Mercury 3 |
|---|---|---|
| DeckBench measured by Spring Prompt · 3 results | ||
| Cost per deckUS dollars, lower is better 11 · 4 of 24 measured | $0.0465 | $0.0116 |
| 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. 24 · 18 of 24 measured | 599 | 812 |
| Accurate decks% of tasks, higher is better 20 · 20 of 24 measured | 0.0% | 0.0% |
| ROASBench measured by Spring Prompt · 3 results | ||
| Overall scorescore out of 100, higher is better 17 · 18 of 24 measured | 28.3 | 26.1 |
| Audience scorescore out of 100, higher is better 20 · 21 of 24 measured | 44.8 | 43.2 |
| Business scorescore out of 100, higher is better 17 · 18 of 24 measured | 23.8 | 17.6 |
Show all 26 results (20 more)
| Measure | DeepSeek-V4-Pro (0423) | Mercury 3 |
|---|---|---|
| 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 14 · 6 of 24 measured | 33.3% | 66.7% |
| Design quality% of the maximum, higher is better 23 · 16 of 24 measured | 40.9% | 58.5% |
| Draft figure quoted% of tasks, lower is better 12 · 12 of 24 measured | 33.3% | 33.3% |
| Findings missing% of tasks, lower is better 17 · 17 of 24 measured | 16.7% | 16.7% |
| 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. 24 · 16 of 24 measured | 24.4% | 44.0% |
| Layout defects% of tasks, lower is better 14 · 6 of 24 measured | 66.7% | 33.3% |
| Misleading metric used% of tasks, lower is better 1 · 22 of 24 measured | 0.0% | 16.7% |
| 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 20 · 22 of 24 measured | 66.7% | 83.3% |
| Slides needing work% of tasks, lower is better 21 · 7 of 24 measured | 83.3% | 33.3% |
| Time per deckseconds, lower is better 21 · 9 of 24 measured | 332 | 83.3 |
| Unsupported claims% of tasks, lower is better 24 · 11 of 24 measured | 66.7% | 16.7% |
| Unsupported numbers% of tasks, lower is better 1 · 20 of 24 measured | 0.0% | 16.7% |
| ROASBench measured by Spring Prompt · 6 results | ||
| Consistency scorescore out of 100, higher is better 22 · 19 of 24 measured | 9.1 | 15.1 |
| Contribution profitsimulated US dollars, higher is better 16 · 18 of 24 measured | $301,289 | $104,868 |
| Cost of a runUS dollars, lower is better 13 · 6 of 24 measured | $0.20 | $0.0533 |
| Months over budgetmonths of 12, lower is better 1 · 1 of 24 measured | 0 | 0 |
| Planning scorescore out of 100, higher is better 22 · 23 of 24 measured | 54.0 | 53.8 |
| Return on ad spendprofit per $1 spent, higher is better 16 · 18 of 24 measured | $0.26 | $0.10 |
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
- Mercury 3 vs Claude Opus 5.5Highest-scoring overall available today
- Mercury 3 vs GPT-6 LunaJust above overall
- Mercury 3 vs GLM-5.3Just below overall
Quick answers
Is DeepSeek-V4-Pro (0423) better than Mercury 3?
Pick Mercury 3: it scores higher (Spring Prompt overall 39 against 31) and costs less.
Which is cheaper, DeepSeek-V4-Pro (0423) or Mercury 3?
Mercury 3 is cheaper to run: $0.012 against $0.046 per deck on DeckBench (4.0 times less).
Which is better for decks from an analysis, DeepSeek-V4-Pro (0423) or Mercury 3?
Mercury 3 ranks 18 of 24 models on sale for turning a finished analysis into a deck you could present as it is, against 24 for DeepSeek-V4-Pro (0423).
Which is better for marketing planning, DeepSeek-V4-Pro (0423) or Mercury 3?
DeepSeek-V4-Pro (0423) ranks 17 of 24 models on sale for planning a year of ad spend without overspending, against 18 for Mercury 3.
Which is better for speed under pressure, DeepSeek-V4-Pro (0423) or Mercury 3?
Mercury 3 ranks 10 of 28 models on sale for good decisions against a real clock (fast chess), against 28 for DeepSeek-V4-Pro (0423).
Which has the bigger context window, DeepSeek-V4-Pro (0423) or Mercury 3?
DeepSeek-V4-Pro (0423): 1,048,576 tokens, against 1,000,000 for Mercury 3.
Run DeepSeek-V4-Pro (0423) and Mercury 3 on your own prompt
Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.