Mercury 2 vs Qwen3.5 397B A17B
Qwen3.5 397B A17B leads Mercury 2 on the Artificial Analysis Intelligence Index, 21.4 to 10.8, and Mercury 2 costs 3.1x less per output token ($0.75 vs $2.34 per million). Updated October 22, 2026; 38 benchmarks have a result for both.
Mercury 2 or Qwen3.5 397B A17B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mercury 2 for output tokens 3.1x cheaper ($0.75 vs $2.34 per million) and work measured by LMArena WebDev or SciCode, where it leads.
- Shared results
- 38
- Mercury 2 only
- 4
- Qwen3.5 397B A17B only
- 27
- Like-for-like categories
- 7 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 21.4 against 10.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mercury 2 has a AA Agentic Index result, 1.6.
Directional only
Web design
Design Arena: websites
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 1190 against 1036.
Same board, both measured
Long documents
Listed context window
Qwen3.5 397B A17B
Qwen3.5 397B A17B takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2
Mercury 2 $0.0006, Qwen3.5 397B A17B $0.0016 per turn.
List prices
At a glance
- Coding index
- Mercury 2 not benchmarked, Qwen3.5 397B A17B not benchmarked.
- Widest category
- Agentic work, 24.9 points apart on average over 1 shared benchmark.
- Widest single gap
- LMArena WebDev: React: Mercury 2 1160 against Qwen3.5 397B A17B 1388, 38.0 points apart on a 0 to 100 scale.
- Output price
- Mercury 2 $0.75 against Qwen3.5 397B A17B $2.34 per million output tokens, 3.1x apart.
- Context window
- Mercury 2 takes 128K tokens, Qwen3.5 397B A17B 262K.
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 | Bars | Qwen3.5 397B A17B | Ties |
|---|---|---|---|---|
| Coding | 1 | 7 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Knowledge | 0 | 3 | ||
| Web design | 0 | 7 | ||
| General | 0 | 13 | ||
| All shared boards | 1 | 37 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index17
| Benchmark | Mercury 2 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LMArena WebDev | 1171 | 1400 | Qwen3.5 397B A17B |
| AA Coding Index | 31.1 | Not measured | Only Mercury 2 measured |
| SciCode | 37.7% | 44.8% | Qwen3.5 397B A17B |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 40.9% | Qwen3.5 397B A17B |
| WeirdML | 43.2% | Not measured | Only Mercury 2 measured |
| ALE-Bench | 785.6 | 621.9 | Mercury 2 |
| LMArena Text: coding | 1390 | 1464 | Qwen3.5 397B A17B |
| LMArena Text: software and IT | 1385 | 1463 | Qwen3.5 397B A17B |
| LMArena WebDev: React | 1160 | 1388 | Qwen3.5 397B A17B |
| LMArena WebDev: HTML | 1199 | 1410 | Qwen3.5 397B A17B |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 21.4 | Qwen3.5 397B A17B |
| Epoch Capabilities Index | Not measured | 146.8 | Only Qwen3.5 397B A17B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | Not measured | Only Mercury 2 measured |
| τ²-Bench Telecom | 70.8% | 95.6% | Qwen3.5 397B A17B |
| APEX-Agents | Not measured | 24.9% | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Mercury 2 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 77.0% | 89.3% | Qwen3.5 397B A17B |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 29.0% | Qwen3.5 397B A17B |
| GPQA Diamond (Epoch AI run) | Not measured | 86.4% | Only Qwen3.5 397B A17B measured |
| Mystery game puzzles | Not measured | 18.0% | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts | 1362 | 1448 | Qwen3.5 397B A17B |
| LMArena Text: expert | 1358 | 1462 | Qwen3.5 397B A17B |
| LMArena Text: hard prompts in English | 1374 | 1450 | Qwen3.5 397B A17B |
| LMArena Vision: diagrams | Not measured | 1277 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: homework | Not measured | 1292 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mercury 2 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 88.9% | Only Qwen3.5 397B A17B measured |
| FrontierMath, tiers 1 to 3 | Not measured | 31.2% | Only Qwen3.5 397B A17B measured |
| LMArena Text: math | Not measured | 1453 | Only Qwen3.5 397B A17B measured |
| LMArena Text: mathematical work | Not measured | 1454 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mercury 2 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LMArena Text: science | 1343 | 1457 | Qwen3.5 397B A17B |
| LMArena Text: medicine and healthcare | 1363 | 1455 | Qwen3.5 397B A17B |
| LMArena Text: legal and government | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: business and finance | 1349 | 1435 | Qwen3.5 397B A17B |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | Mercury 2 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Design Arena: websites | 1036 | 1190 | Qwen3.5 397B A17B |
| Design Arena: UI components | 996 | 1160 | Qwen3.5 397B A17B |
| Design Arena: game dev | 984 | 1140 | Qwen3.5 397B A17B |
| Design Arena: data viz | 1009 | 1175 | Qwen3.5 397B A17B |
| Design Arena: 3D | 982 | 1160 | Qwen3.5 397B A17B |
| Design Arena: all code categories | 1021 | 1179 | Qwen3.5 397B A17B |
| Design Arena: SVG | 998 | 1139 | Qwen3.5 397B A17B |
| Design Arena: ASCII art | 988 | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index013
| Benchmark | Mercury 2 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| IFBench | 69.8% | 78.8% | Qwen3.5 397B A17B |
| Long context reasoning (AA-LCR) | 43.7% | 77.3% | Qwen3.5 397B A17B |
| DTBench | Not measured | 87.5% | Only Qwen3.5 397B A17B measured |
| LMCA | Not measured | 37.9% | Only Qwen3.5 397B A17B measured |
| LMArena Text | 1354 | 1437 | Qwen3.5 397B A17B |
| LMArena Text: instruction following | 1328 | 1424 | Qwen3.5 397B A17B |
| LMArena Text: creative writing | 1286 | 1402 | Qwen3.5 397B A17B |
| LMArena Vision | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Text: English | 1378 | 1443 | Qwen3.5 397B A17B |
| LMArena Text: non-English | 1330 | 1430 | Qwen3.5 397B A17B |
| LMArena Text: Chinese | 1414 | 1498 | Qwen3.5 397B A17B |
| LMArena Text: German | Not measured | 1445 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Japanese | Not measured | 1429 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Korean | Not measured | 1384 | Only Qwen3.5 397B A17B measured |
| LMArena Text: French | Not measured | 1462 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Spanish | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Russian | 1304 | 1430 | Qwen3.5 397B A17B |
| LMArena Text: Polish | Not measured | 1447 | Only Qwen3.5 397B A17B measured |
| LMArena Text: multi-turn | 1357 | 1446 | Qwen3.5 397B A17B |
| LMArena Text: longer queries | 1329 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: writing and language | 1300 | 1415 | Qwen3.5 397B A17B |
| LMArena Text: entertainment and media | 1314 | 1399 | Qwen3.5 397B A17B |
| LMArena Vision: English | Not measured | 1268 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: Chinese | Not measured | 1314 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: reading text | Not measured | 1271 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: humor | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: captioning | Not measured | 1230 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: recognizing things | Not measured | 1265 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: creative writing | Not measured | 1260 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2 | Qwen3.5 397B A17B | 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 costs less
Repository review
50K input + 3K output tokens
Mercury 2 costs less
Agent loop
200K input + 10K output tokens
Mercury 2 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 | Qwen3.5 397B A17B |
|---|---|---|
| Maker | Inception | Qwen |
| Weights | No public weights listed | Open weights |
| Released | March 4, 2026 | February 16, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $0.25 | $0.39 |
| Output $/Mtok | $0.75 | $2.34 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2 better than Qwen3.5 397B A17B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mercury 2 for output tokens 3.1x cheaper ($0.75 vs $2.34 per million) and work measured by LMArena WebDev or SciCode, where it leads.
Which is cheaper, Mercury 2 or Qwen3.5 397B A17B?
Mercury 2 costs $0.25 per million input tokens and $0.75 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for neither of them.
Which has the bigger context window, Mercury 2 or Qwen3.5 397B A17B?
Qwen3.5 397B A17B, with 262K tokens against 128K.
How many benchmarks is the Mercury 2 vs Qwen3.5 397B A17B comparison based on?
38 benchmarks have a result for both models as of October 22, 2026. Mercury 2's coding index rests on 1 independent benchmark and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.