Mercury 2 vs Qwen3.6 27B
Qwen3.6 27B leads Mercury 2 on the Artificial Analysis Intelligence Index, 21.4 to 10.8, and Mercury 2 costs 3.6x less per output token ($0.75 vs $2.70 per million). Updated October 22, 2026; 10 benchmarks have a result for both.
Mercury 2 or Qwen3.6 27B: which to pick
Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; Mercury 2 has none, so the two cannot be ranked on coding.
Pick Mercury 2 for output tokens 3.6x cheaper ($0.75 vs $2.70 per million) and work measured by IFBench, where it leads.
- Shared results
- 10
- Mercury 2 only
- 32
- Qwen3.6 27B only
- 14
- 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
No call
Only Qwen3.6 27B has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.6 27B
Qwen3.6 27B leads, 21.4 against 10.8.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.6 27B
Qwen3.6 27B leads, 18.5 against 1.6.
Same board, both measured
Web design
Design Arena: websites
No call
Only Mercury 2 has a Design Arena: websites result, 1035.
Directional only
Long documents
Listed context window
Qwen3.6 27B
Qwen3.6 27B takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2
Mercury 2 $0.0006, Qwen3.6 27B $0.0018 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.6 27B has the number, $1.30.
Directional only
At a glance
- Coding index
- Mercury 2 not benchmarked, Qwen3.6 27B 36.8 from 2 benchmarks.
- Widest category
- Agentic work, 20.1 points apart on average over 2 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Mercury 2 43.7% against Qwen3.6 27B 77.3%, 33.7 points apart on a 0 to 100 scale.
- Output price
- Mercury 2 $0.75 against Qwen3.6 27B $2.70 per million output tokens, 3.6x apart.
- Context window
- Mercury 2 takes 128K tokens, Qwen3.6 27B 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 | Qwen3.6 27B | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 0 | 2 | ||
| General | 1 | 1 | ||
| All shared boards | 1 | 9 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Mercury 2 | Qwen3.6 27B | Leader |
|---|---|---|---|
| LMArena WebDev | 1171 | Not measured | Only Mercury 2 measured |
| AA Coding Index | 31.1 | 53.7 | Qwen3.6 27B |
| SWE-bench Verified (Vals AI) | Not measured | 70.0% | Only Qwen3.6 27B measured |
| Vibe Code Bench (Vals AI) | Not measured | 11.9% | Only Qwen3.6 27B measured |
| SciCode | 37.7% | 42.8% | Qwen3.6 27B |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 34.8% | Qwen3.6 27B |
| WeirdML | 43.2% | Not measured | Only Mercury 2 measured |
| ALE-Bench | 785.6 | Not measured | Only Mercury 2 measured |
| LMArena Text: coding | 1390 | Not measured | Only Mercury 2 measured |
| LMArena Text: software and IT | 1385 | Not measured | Only Mercury 2 measured |
| LMArena WebDev: React | 1160 | Not measured | Only Mercury 2 measured |
| LMArena WebDev: HTML | 1199 | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2 | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 21.4 | Qwen3.6 27B |
| Epoch Capabilities Index | Not measured | 146.2 | Only Qwen3.6 27B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mercury 2 | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | 18.5 | Qwen3.6 27B |
| τ²-Bench Telecom | 70.8% | 94.2% | Qwen3.6 27B |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mercury 2 | Qwen3.6 27B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 77.0% | 84.2% | Qwen3.6 27B |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 23.1% | Qwen3.6 27B |
| GPQA Diamond (Epoch AI run) | Not measured | 85.9% | Only Qwen3.6 27B measured |
| Mystery game puzzles | Not measured | 7.0% | Only Qwen3.6 27B measured |
| LMArena Text: hard prompts | 1362 | Not measured | Only Mercury 2 measured |
| LMArena Text: expert | 1358 | Not measured | Only Mercury 2 measured |
| LMArena Text: hard prompts in English | 1374 | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mercury 2 | Qwen3.6 27B | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 91.1% | Only Qwen3.6 27B measured |
| FrontierMath, tiers 1 to 3 | Not measured | 35.1% | Only Qwen3.6 27B measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Mercury 2 | Qwen3.6 27B | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | Not measured | 53.2% | Only Qwen3.6 27B measured |
| CorpFin (Vals AI) | Not measured | 62.3% | Only Qwen3.6 27B measured |
| TaxEval (Vals AI) | Not measured | 71.3% | Only Qwen3.6 27B measured |
| MortgageTax (Vals AI) | Not measured | 68.3% | Only Qwen3.6 27B measured |
| LMArena Text: science | 1343 | Not measured | Only Mercury 2 measured |
| LMArena Text: medicine and healthcare | 1363 | Not measured | Only Mercury 2 measured |
| LMArena Text: business and finance | 1349 | Not measured | Only Mercury 2 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 | Qwen3.6 27B | Leader |
|---|---|---|---|
| Design Arena: websites | 1035 | Not measured | Only Mercury 2 measured |
| Design Arena: UI components | 996 | Not measured | Only Mercury 2 measured |
| Design Arena: game dev | 983 | Not measured | Only Mercury 2 measured |
| Design Arena: data viz | 1010 | Not measured | Only Mercury 2 measured |
| Design Arena: 3D | 982 | Not measured | Only Mercury 2 measured |
| Design Arena: all code categories | 1020 | Not measured | Only Mercury 2 measured |
| Design Arena: SVG | 996 | Not measured | Only Mercury 2 measured |
| 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 index11
| Benchmark | Mercury 2 | Qwen3.6 27B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 45.6% | Only Qwen3.6 27B measured |
| IFBench | 69.8% | 67.6% | Mercury 2 |
| Long context reasoning (AA-LCR) | 43.7% | 77.3% | Qwen3.6 27B |
| DTBench | Not measured | 78.1% | Only Qwen3.6 27B measured |
| LMCA | Not measured | 34.5% | Only Qwen3.6 27B measured |
| LMArena Text | 1354 | Not measured | Only Mercury 2 measured |
| LMArena Text: instruction following | 1328 | Not measured | Only Mercury 2 measured |
| LMArena Text: creative writing | 1286 | Not measured | Only Mercury 2 measured |
| LMArena Text: English | 1378 | Not measured | Only Mercury 2 measured |
| LMArena Text: non-English | 1330 | Not measured | Only Mercury 2 measured |
| LMArena Text: Chinese | 1414 | Not measured | Only Mercury 2 measured |
| LMArena Text: Russian | 1304 | Not measured | Only Mercury 2 measured |
| LMArena Text: multi-turn | 1357 | Not measured | Only Mercury 2 measured |
| LMArena Text: longer queries | 1329 | Not measured | Only Mercury 2 measured |
| LMArena Text: writing and language | 1300 | Not measured | Only Mercury 2 measured |
| LMArena Text: entertainment and media | 1314 | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 30 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2 | Qwen3.6 27B | 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 | Qwen3.6 27B |
|---|---|---|
| Maker | Inception | Qwen |
| Weights | No public weights listed | Open weights |
| Released | March 4, 2026 | April 27, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $0.25 | $0.45 |
| Output $/Mtok | $0.75 | $2.70 |
| Coding index | Not benchmarked | 36.8 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | $1.30 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2 better than Qwen3.6 27B for coding?
Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; Mercury 2 has none, so the two cannot be ranked on coding. Pick Mercury 2 for output tokens 3.6x cheaper ($0.75 vs $2.70 per million) and work measured by IFBench, where it leads.
Which is cheaper, Mercury 2 or Qwen3.6 27B?
Mercury 2 costs $0.25 per million input tokens and $0.75 per million output tokens; Qwen3.6 27B costs $0.45 and $2.70. Cost per solved task is known for Qwen3.6 27B only.
Which has the bigger context window, Mercury 2 or Qwen3.6 27B?
Qwen3.6 27B, with 262K tokens against 128K.
How many benchmarks is the Mercury 2 vs Qwen3.6 27B comparison based on?
10 benchmarks have a result for both models as of October 22, 2026. Mercury 2's coding index rests on 1 independent benchmark and Qwen3.6 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.