Mercury 2.5 vs MiniMax M3.1 Flash
MiniMax M3.1 Flash leads Mercury 2.5 on coding, 59.0 to 1.6 on the Vibe Coding Index, and Mercury 2.5 costs 4.0x less per output token ($0.15 vs $0.60 per million). Updated October 22, 2026; 8 benchmarks have a result for both.
Mercury 2.5 or MiniMax M3.1 Flash: which to pick
Pick MiniMax M3.1 Flash for coding: it scores 59.0 on the Vibe Coding Index against 1.6 for Mercury 2.5.
Pick Mercury 2.5 for output tokens 4.0x cheaper ($0.15 vs $0.60 per million).
- Shared results
- 8
- Mercury 2.5 only
- 14
- MiniMax M3.1 Flash only
- 12
- Like-for-like categories
- 5 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
MiniMax M3.1 Flash
MiniMax M3.1 Flash scores 59.0 against 1.6.
2 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiniMax M3.1 Flash
MiniMax M3.1 Flash leads, 42.7 against 12.3.
Same board, both measured
General
Vals Index
No call
Only MiniMax M3.1 Flash has a Vals Index result, 53.8%.
Directional only
Long documents
Listed context window
MiniMax M3.1 Flash
MiniMax M3.1 Flash takes 1M tokens against 260K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
Mercury 2.5 $0.0001, MiniMax M3.1 Flash $0.0004 per turn.
List prices
At a glance
- Coding index
- Mercury 2.5 1.6 from 2 benchmarks, MiniMax M3.1 Flash 59.0 from 4 benchmarks.
- Widest category
- Coding, 39.6 points apart on average over 3 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Mercury 2.5 3.7% against MiniMax M3.1 Flash 73.9%, 70.3 points apart on a 0 to 100 scale.
- Output price
- Mercury 2.5 $0.15 against MiniMax M3.1 Flash $0.60 per million output tokens, 4.0x apart.
- Context window
- Mercury 2.5 takes 260K tokens, MiniMax M3.1 Flash 1M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Mercury 2.5 | Bars | MiniMax M3.1 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Mercury 2.5 | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 83.9% | Only MiniMax M3.1 Flash measured |
| LMArena WebDev | Not measured | 1587 | Only MiniMax M3.1 Flash measured |
| Terminal-Bench 4 (Vals AI) | 0.0% | 25.3% | MiniMax M3.1 Flash |
| Vibe Code Bench (Vals AI) | 3.7% | 73.9% | MiniMax M3.1 Flash |
| Code migration (Vals AI) | 4.5% | Not measured | Only Mercury 2.5 measured |
| IOI (Vals AI) | 2.4% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 34.5% | Not measured | Only Mercury 2.5 measured |
| SkillsBench (Vals AI) | 18.1% | Not measured | Only Mercury 2.5 measured |
| CyberBench (Vals AI) | 45.5% | Not measured | Only Mercury 2.5 measured |
| SciCode | 38.5% | 53.4% | MiniMax M3.1 Flash |
| ALE-Bench | 301.6 | Not measured | Only Mercury 2.5 measured |
| LMArena WebDev: React | Not measured | 1609 | Only MiniMax M3.1 Flash measured |
| LMArena WebDev: HTML | Not measured | 1529 | Only MiniMax M3.1 Flash measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2.5 | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.3 | 42.7 | MiniMax M3.1 Flash |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mercury 2.5 | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 72.7% | Only MiniMax M3.1 Flash measured |
| LiveBench browser | Not measured | 92.0% | Only MiniMax M3.1 Flash measured |
| LiveBench long agentic | Not measured | 34.7% | Only MiniMax M3.1 Flash measured |
| Finance Agent (Vals AI) | 18.9% | Not measured | Only Mercury 2.5 measured |
| Tax Agent Bench (Vals AI) | 2.5% | 32.1% | MiniMax M3.1 Flash |
| Legal Research Bench (Vals AI) | 4.3% | 34.1% | MiniMax M3.1 Flash |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 7.5% | Only MiniMax M3.1 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 8.8% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2.5 | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 82.9% | Only MiniMax M3.1 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 11.8% | 48.0% | MiniMax M3.1 Flash |
| Neither model has a result on the other 21 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mercury 2.5 | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| ProofBench | 3.0% | Not measured | Only Mercury 2.5 measured |
| Neither model has a result on the other 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mercury 2.5 | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.1% | Not measured | Only Mercury 2.5 measured |
| MedCode (Vals AI) | 31.3% | Not measured | Only Mercury 2.5 measured |
| Neither model has a result on the other 18 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mercury 2.5 | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| LiveBench design | Not measured | 74.0% | Only MiniMax M3.1 Flash measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2.5 | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| Vals Index | Not measured | 53.8% | Only MiniMax M3.1 Flash measured |
| LiveBench data analysis | Not measured | 71.4% | Only MiniMax M3.1 Flash measured |
| Public Benefits Bench (Vals AI) | 45.3% | Not measured | Only Mercury 2.5 measured |
| MedScribe (Vals AI) | 55.1% | Not measured | Only Mercury 2.5 measured |
| Long context reasoning (AA-LCR) | 71.7% | 79.7% | MiniMax M3.1 Flash |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2.5 | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Mercury 2.5 costs less
Repository review
50K input + 3K output tokens
Mercury 2.5 costs less
Agent loop
200K input + 10K output tokens
Mercury 2.5 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Inception Mercury 2.5 | MiniMax M3.1 Flash |
|---|---|---|
| Maker | Inception | MiniMax |
| Weights | No public weights listed | No public weights listed |
| Released | September 8, 2026 | October 19, 2026 |
| Context window | 260K | 1M |
| Input $/Mtok | $0.04 | $0.15 |
| Output $/Mtok | $0.15 | $0.60 |
| Coding index | 1.6 | 59.0 |
| Independent measurements behind it | 2 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2.5 better than MiniMax M3.1 Flash for coding?
Pick MiniMax M3.1 Flash for coding: it scores 59.0 on the Vibe Coding Index against 1.6 for Mercury 2.5. Pick Mercury 2.5 for output tokens 4.0x cheaper ($0.15 vs $0.60 per million).
Which is cheaper, Mercury 2.5 or MiniMax M3.1 Flash?
Mercury 2.5 costs $0.04 per million input tokens and $0.15 per million output tokens; MiniMax M3.1 Flash costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Mercury 2.5 or MiniMax M3.1 Flash?
MiniMax M3.1 Flash, with 1M tokens against 260K.
How many benchmarks is the Mercury 2.5 vs MiniMax M3.1 Flash comparison based on?
8 benchmarks have a result for both models as of October 22, 2026. Mercury 2.5's coding index rests on 2 independent benchmarks and MiniMax M3.1 Flash's on 4. Where only one model has a result, the page says so instead of naming a winner.