Mercury 2.5 vs Qwen3.7 Plus
Qwen3.7 Plus leads Mercury 2.5 on coding, 33.2 to 1.6 on the Vibe Coding Index, and Mercury 2.5 costs 8.5x less per output token ($0.15 vs $1.28 per million). Updated October 22, 2026; 12 benchmarks have a result for both.
Mercury 2.5 or Qwen3.7 Plus: which to pick
Pick Qwen3.7 Plus for coding: it scores 33.2 on the Vibe Coding Index against 1.6 for Mercury 2.5.
Pick Mercury 2.5 for output tokens 8.5x cheaper ($0.15 vs $1.28 per million).
- Shared results
- 12
- Mercury 2.5 only
- 10
- Qwen3.7 Plus only
- 63
- 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
Qwen3.7 Plus
Qwen3.7 Plus scores 33.2 against 1.6.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Qwen3.7 Plus
Qwen3.7 Plus leads, 25.2 against 12.3.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.7 Plus has a AA Agentic Index result, 17.5.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3.7 Plus has a Design Arena: websites result, 1269.
Directional only
Long documents
Listed context window
Qwen3.7 Plus
Qwen3.7 Plus takes 1M tokens against 260K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
Mercury 2.5 $0.0001, Qwen3.7 Plus $0.0010 per turn.
List prices
At a glance
- Coding index
- Mercury 2.5 1.6 from 2 benchmarks, Qwen3.7 Plus 33.2 from 2 benchmarks.
- Widest category
- Reasoning, 23.8 points apart on average over 1 shared benchmark.
- Widest single gap
- Vibe Code Bench (Vals AI): Mercury 2.5 3.7% against Qwen3.7 Plus 46.4%, 42.7 points apart on a 0 to 100 scale.
- Output price
- Mercury 2.5 $0.15 against Qwen3.7 Plus $1.28 per million output tokens, 8.5x apart.
- Context window
- Mercury 2.5 takes 260K tokens, Qwen3.7 Plus 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 | Qwen3.7 Plus | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 4 | ||
| Reasoning | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 12 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | Mercury 2.5 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 55.9 | Only Qwen3.7 Plus measured |
| Terminal-Bench 4 (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | 3.7% | 46.4% | Qwen3.7 Plus |
| Code migration (Vals AI) | 4.5% | 12.9% | Qwen3.7 Plus |
| IOI (Vals AI) | 2.4% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 34.5% | 52.8% | Qwen3.7 Plus |
| SkillsBench (Vals AI) | 18.1% | 54.3% | Qwen3.7 Plus |
| CyberBench (Vals AI) | 45.5% | Not measured | Only Mercury 2.5 measured |
| SciCode | 38.5% | 46.1% | Qwen3.7 Plus |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 47.0% | Only Qwen3.7 Plus measured |
| FrontierCode | Not measured | 10.2% | Only Qwen3.7 Plus measured |
| ALE-Bench | 301.6 | Not measured | Only Mercury 2.5 measured |
| LMArena Text: coding | Not measured | 1473 | Only Qwen3.7 Plus measured |
| LMArena Text: software and IT | Not measured | 1473 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2.5 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.3 | 25.2 | Qwen3.7 Plus |
| Epoch Capabilities Index | Not measured | 147.0 | Only Qwen3.7 Plus measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Mercury 2.5 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 17.5 | Only Qwen3.7 Plus measured |
| Finance Agent (Vals AI) | 18.9% | 38.2% | Qwen3.7 Plus |
| Tax Agent Bench (Vals AI) | 2.5% | 10.5% | Qwen3.7 Plus |
| Legal Research Bench (Vals AI) | 4.3% | 16.4% | Qwen3.7 Plus |
| Excel Modeling Benchmark (Vals AI) | 8.8% | 49.3% | Qwen3.7 Plus |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| τ²-Bench Telecom | Not measured | 93.0% | Only Qwen3.7 Plus measured |
| OSWorld 2.0 | Not measured | 2.8% | Only Qwen3.7 Plus 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 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 90.0% | Only Qwen3.7 Plus measured |
| Humanity's Last Exam (Artificial Analysis run) | 11.8% | 35.6% | Qwen3.7 Plus |
| GPQA Diamond (Epoch AI run) | Not measured | 87.9% | Only Qwen3.7 Plus measured |
| Mystery game puzzles | Not measured | 17.0% | Only Qwen3.7 Plus measured |
| LMArena Text: hard prompts | Not measured | 1460 | Only Qwen3.7 Plus measured |
| LMArena Text: expert | Not measured | 1466 | Only Qwen3.7 Plus measured |
| LMArena Text: hard prompts in English | Not measured | 1460 | Only Qwen3.7 Plus measured |
| LMArena Vision: diagrams | Not measured | 1292 | Only Qwen3.7 Plus measured |
| LMArena Vision: homework | Not measured | 1295 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Mercury 2.5 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 93.3% | Only Qwen3.7 Plus measured |
| FrontierMath, tiers 1 to 3 | Not measured | 34.4% | Only Qwen3.7 Plus measured |
| ProofBench | 3.0% | Not measured | Only Mercury 2.5 measured |
| LMArena Text: math | Not measured | 1467 | Only Qwen3.7 Plus measured |
| LMArena Text: mathematical work | Not measured | 1470 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Mercury 2.5 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.1% | Not measured | Only Mercury 2.5 measured |
| MortgageTax (Vals AI) | Not measured | 66.2% | Only Qwen3.7 Plus measured |
| MedCode (Vals AI) | 31.3% | Not measured | Only Mercury 2.5 measured |
| LMArena Text: science | Not measured | 1464 | Only Qwen3.7 Plus measured |
| LMArena Text: medicine and healthcare | Not measured | 1464 | Only Qwen3.7 Plus measured |
| LMArena Text: legal and government | Not measured | 1451 | Only Qwen3.7 Plus measured |
| LMArena Text: business and finance | Not measured | 1435 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mercury 2.5 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1269 | Only Qwen3.7 Plus measured |
| Design Arena: UI components | Not measured | 1258 | Only Qwen3.7 Plus measured |
| Design Arena: game dev | Not measured | 1261 | Only Qwen3.7 Plus measured |
| Design Arena: data viz | Not measured | 1276 | Only Qwen3.7 Plus measured |
| Design Arena: 3D | Not measured | 1238 | Only Qwen3.7 Plus measured |
| Design Arena: all code categories | Not measured | 1269 | Only Qwen3.7 Plus measured |
| Design Arena: SVG | Not measured | 1208 | Only Qwen3.7 Plus measured |
| Design Arena: ASCII art | Not measured | 1143 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2.5 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 45.3% | Not measured | Only Mercury 2.5 measured |
| SAGE (Vals AI) | Not measured | 39.3% | Only Qwen3.7 Plus measured |
| MedScribe (Vals AI) | 55.1% | Not measured | Only Mercury 2.5 measured |
| Vals Multimodal Index | Not measured | 53.9% | Only Qwen3.7 Plus measured |
| IFBench | Not measured | 78.0% | Only Qwen3.7 Plus measured |
| Long context reasoning (AA-LCR) | 71.7% | 73.0% | Qwen3.7 Plus |
| DTBench | Not measured | 84.0% | Only Qwen3.7 Plus measured |
| LMCA | Not measured | 37.6% | Only Qwen3.7 Plus measured |
| LMArena Text | Not measured | 1454 | Only Qwen3.7 Plus measured |
| LMArena Text: instruction following | Not measured | 1439 | Only Qwen3.7 Plus measured |
| LMArena Text: creative writing | Not measured | 1438 | Only Qwen3.7 Plus measured |
| LMArena Vision | Not measured | 1278 | Only Qwen3.7 Plus measured |
| LMArena Text: English | Not measured | 1458 | Only Qwen3.7 Plus measured |
| LMArena Text: non-English | Not measured | 1445 | Only Qwen3.7 Plus measured |
| LMArena Text: Chinese | Not measured | 1509 | Only Qwen3.7 Plus measured |
| LMArena Text: German | Not measured | 1471 | Only Qwen3.7 Plus measured |
| LMArena Text: Japanese | Not measured | 1412 | Only Qwen3.7 Plus measured |
| LMArena Text: Korean | Not measured | 1413 | Only Qwen3.7 Plus measured |
| LMArena Text: French | Not measured | 1472 | Only Qwen3.7 Plus measured |
| LMArena Text: Spanish | Not measured | 1457 | Only Qwen3.7 Plus measured |
| LMArena Text: Russian | Not measured | 1457 | Only Qwen3.7 Plus measured |
| LMArena Text: Polish | Not measured | 1449 | Only Qwen3.7 Plus measured |
| LMArena Text: multi-turn | Not measured | 1459 | Only Qwen3.7 Plus measured |
| LMArena Text: longer queries | Not measured | 1454 | Only Qwen3.7 Plus measured |
| LMArena Text: writing and language | Not measured | 1437 | Only Qwen3.7 Plus measured |
| LMArena Text: entertainment and media | Not measured | 1422 | Only Qwen3.7 Plus measured |
| LMArena Vision: English | Not measured | 1280 | Only Qwen3.7 Plus measured |
| LMArena Vision: Chinese | Not measured | 1332 | Only Qwen3.7 Plus measured |
| LMArena Vision: reading text | Not measured | 1288 | Only Qwen3.7 Plus measured |
| LMArena Vision: humor | Not measured | 1261 | Only Qwen3.7 Plus measured |
| LMArena Vision: creative writing | Not measured | 1258 | Only Qwen3.7 Plus measured |
| LMArena Document | Not measured | 1444 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2.5 | Qwen3.7 Plus | 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 | Qwen3.7 Plus |
|---|---|---|
| Maker | Inception | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | September 8, 2026 | June 3, 2026 |
| Context window | 260K | 1M |
| Input $/Mtok | $0.04 | $0.32 |
| Output $/Mtok | $0.15 | $1.28 |
| Coding index | 1.6 | 33.2 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2.5 better than Qwen3.7 Plus for coding?
Pick Qwen3.7 Plus for coding: it scores 33.2 on the Vibe Coding Index against 1.6 for Mercury 2.5. Pick Mercury 2.5 for output tokens 8.5x cheaper ($0.15 vs $1.28 per million).
Which is cheaper, Mercury 2.5 or Qwen3.7 Plus?
Mercury 2.5 costs $0.04 per million input tokens and $0.15 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for neither of them.
Which has the bigger context window, Mercury 2.5 or Qwen3.7 Plus?
Qwen3.7 Plus, with 1M tokens against 260K.
How many benchmarks is the Mercury 2.5 vs Qwen3.7 Plus comparison based on?
12 benchmarks have a result for both models as of October 22, 2026. Mercury 2.5's coding index rests on 2 independent benchmarks and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.