Model comparison
DeepSeek V4 Flash vs Mercury 2.5
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 33.5 on the Noometry Index. Mercury 2.5 costs 3.9× less per token, which makes it the better buy when DeepSeek V4 Flash's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
DeepSeekSummary
- They share 4 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 3 categories and Mercury 2.5 in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek V4 Flash leads 60.3 to 23.3.
- The biggest single-benchmark swing is ProofBench: 56% for DeepSeek V4 Flash and 3% for Mercury 2.5.
- Mercury 2.5 is cheaper at $0.04 / $0.15 per million input/output tokens, against $0.15 / $0.60 for DeepSeek V4 Flash.
- DeepSeek V4 Flash accepts more context: 1M tokens versus 260K.
- DeepSeek V4 Flash has downloadable open weights; the other is API-only.
Side by side
| DeepSeek V4 Flash | Mercury 2.5 | |
|---|---|---|
| Provider | DeepSeek | Inception |
| Noometry Index | 53.6 | 33.5 |
| Released | 2026-04-24 | 2026-09-08 |
| Weights | Open | Proprietary |
| Context window | 1M | 260K |
| Max output | 393K | 66K |
| Input $ / M tokens | $0.15 | $0.04 |
| Output $ / M tokens | $0.60 | $0.15 |
| Results tracked | 41 | 4 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding DeepSeek V4 Flash leads
DeepSeek V4 Flash: 47.9 (#59), Mercury 2.5: 39.5 (#156)
| Benchmark | DeepSeek V4 Flash | Mercury 2.5 |
|---|---|---|
| SciCode | 49.9% | 38.5% |
| ALE-Bench | 1,306 | 301.65 |
| FrontierCode | 18.8% | — |
| LMArena WebDev | 1582 | — |
| WeirdML | 63% | — |
| LMArena Coding | 1457 | — |
Reasoning DeepSeek V4 Flash leads
DeepSeek V4 Flash: 53.7 (#30), Mercury 2.5: 22.4 (#193)
| Benchmark | DeepSeek V4 Flash | Mercury 2.5 |
|---|---|---|
| CritPt | 16.6% | 0% |
| ARC-AGI-2 | 61.4% | — |
| SimpleBench | 61.1% | — |
| Kagi LLM Benchmark | 52.2% | — |
| NYT Connections (extended) | 89.6% | — |
| ARC-AGI-1 | 89% | — |
| Chess Puzzles | 33% | — |
| LMArena Hard Prompts | 1444 | — |
| Mystery Game Puzzles | 34% | — |
| DTBench | 90.9% | — |
| LMCA | 41.7% | — |
| Epoch Capabilities Index | 154.49 | — |
Math DeepSeek V4 Flash leads
DeepSeek V4 Flash: 60.3 (#37), Mercury 2.5: 23.3 (#272)
| Benchmark | DeepSeek V4 Flash | Mercury 2.5 |
|---|---|---|
| ProofBench | 56% | 3% |
| FrontierMath (Tiers 1-3) | 57.5% | — |
| FrontierMath Tier 4 | 24.4% | — |
| MathArena Final-Answer Competitions | 76.5% | — |
| OTIS Mock AIME 2024-2025 | 94.4% | — |
| LMArena Math | 1427 | — |
Knowledge Not comparable
DeepSeek V4 Flash: 55.4 (#48), Mercury 2.5: —
| Benchmark | DeepSeek V4 Flash | Mercury 2.5 |
|---|---|---|
| GPQA Diamond | 91% | — |
| SimpleQA Verified | 33.6% | — |
| LMArena Expert | 1441 | — |
Multilingual Not comparable
DeepSeek V4 Flash: 53.0 (#72), Mercury 2.5: —
| Benchmark | DeepSeek V4 Flash | Mercury 2.5 |
|---|---|---|
| LMArena Non-English | 1420 | — |
| LMArena Chinese | 1468 | — |
| LMArena French | 1439 | — |
| LMArena German | 1418 | — |
| LMArena Japanese | 1406 | — |
| LMArena Korean | 1384 | — |
| LMArena Russian | 1428 | — |
| LMArena Spanish | 1436 | — |
Instruction Following Not comparable
DeepSeek V4 Flash: 74.9 (#81), Mercury 2.5: —
| Benchmark | DeepSeek V4 Flash | Mercury 2.5 |
|---|---|---|
| LMArena Instruction Following | 1421 | — |
Long Context Not comparable
DeepSeek V4 Flash: 43.8 (#85), Mercury 2.5: —
| Benchmark | DeepSeek V4 Flash | Mercury 2.5 |
|---|---|---|
| LMArena Longer Query | 1434 | — |
Writing & Preference Not comparable
DeepSeek V4 Flash: 63.8 (#61), Mercury 2.5: —
| Benchmark | DeepSeek V4 Flash | Mercury 2.5 |
|---|---|---|
| LMArena Text | 1432 | — |
| LMArena Creative Writing | 1403 | — |
| EQ-Bench Creative Writing | 1559 | — |
| LMArena Multi-Turn | 1449 | — |
Frequently asked questions
Is DeepSeek V4 Flash better than Mercury 2.5?
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 33.5 on the Noometry Index. Mercury 2.5 costs 3.9× less per token, which makes it the better buy when DeepSeek V4 Flash's lead doesn't matter for your workload.
Which is cheaper, DeepSeek V4 Flash or Mercury 2.5?
Mercury 2.5 is cheaper. It lists at $0.04 per million input tokens and $0.15 per million output tokens; DeepSeek V4 Flash lists at $0.15 and $0.60.
Is DeepSeek V4 Flash or Mercury 2.5 better for coding?
DeepSeek V4 Flash scores higher on coding benchmarks: 47.9 versus 39.5 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4 Flash does, with 1M tokens against 260K.
How many benchmarks do DeepSeek V4 Flash and Mercury 2.5 share?
4 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Mercury 2.5 has 4.