Mercury 2 vs Qwen3 VL 30B A3B Instruct
Mercury 2 leads Qwen3 VL 30B A3B Instruct on the Artificial Analysis Intelligence Index, 10.8 to 7.9, at about the same output price ($0.75 vs $0.70 per million). Updated October 22, 2026; 6 benchmarks have a result for both.
Mercury 2 or Qwen3 VL 30B A3B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 6
- Mercury 2 only
- 36
- Qwen3 VL 30B A3B Instruct only
- 4
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Mercury 2
Mercury 2 leads, 10.8 against 7.9.
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
No call
Only Mercury 2 has a Design Arena: websites result, 1035.
Directional only
Long documents
Listed context window
Qwen3 VL 30B A3B Instruct
Qwen3 VL 30B A3B Instruct takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 VL 30B A3B Instruct
Mercury 2 $0.0006, Qwen3 VL 30B A3B Instruct $0.0006 per turn.
List prices
At a glance
- Coding index
- Mercury 2 not benchmarked, Qwen3 VL 30B A3B Instruct not benchmarked.
- Widest category
- Agentic work, 50.9 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Mercury 2 70.8% against Qwen3 VL 30B A3B Instruct 19.9%, 50.9 points apart on a 0 to 100 scale.
- Output price
- Mercury 2 $0.75 against Qwen3 VL 30B A3B Instruct $0.70 per million output tokens, 1.1x apart.
- Context window
- Mercury 2 takes 128K tokens, Qwen3 VL 30B A3B Instruct 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 VL 30B A3B Instruct | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 6 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Mercury 2 | Qwen3 VL 30B A3B Instruct | Leader |
|---|---|---|---|
| LMArena WebDev | 1171 | Not measured | Only Mercury 2 measured |
| AA Coding Index | 31.1 | Not measured | Only Mercury 2 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 69.7% | Only Qwen3 VL 30B A3B Instruct measured |
| SciCode | 37.7% | Not measured | Only Mercury 2 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 6.1% | Mercury 2 |
| 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 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2 | Qwen3 VL 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 7.9 | Mercury 2 |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2 | Qwen3 VL 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | Not measured | Only Mercury 2 measured |
| τ²-Bench Telecom | 70.8% | 19.9% | Mercury 2 |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mercury 2 | Qwen3 VL 30B A3B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 77.0% | 72.0% | Mercury 2 |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 8.9% | Mercury 2 |
| 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 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mercury 2 | Qwen3 VL 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 82.3 | Only Qwen3 VL 30B A3B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 82.3% | Only Qwen3 VL 30B A3B Instruct measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mercury 2 | Qwen3 VL 30B A3B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 80.7% | Only Qwen3 VL 30B A3B Instruct 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 14 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mercury 2 | Qwen3 VL 30B A3B Instruct | 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 index10
| Benchmark | Mercury 2 | Qwen3 VL 30B A3B Instruct | Leader |
|---|---|---|---|
| IFBench | 69.8% | 45.1% | Mercury 2 |
| Long context reasoning (AA-LCR) | 43.7% | Not measured | Only Mercury 2 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 33 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2 | Qwen3 VL 30B A3B Instruct | 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
Qwen3 VL 30B A3B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen3 VL 30B A3B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen3 VL 30B A3B Instruct 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 VL 30B A3B Instruct |
|---|---|---|
| Maker | Inception | Qwen |
| Weights | No public weights listed | Open weights |
| Released | March 4, 2026 | October 6, 2025 |
| Context window | 128K | 262K |
| Input $/Mtok | $0.25 | $0.20 |
| Output $/Mtok | $0.75 | $0.70 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2 better than Qwen3 VL 30B A3B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Mercury 2 or Qwen3 VL 30B A3B Instruct?
Mercury 2 costs $0.25 per million input tokens and $0.75 per million output tokens; Qwen3 VL 30B A3B Instruct costs $0.20 and $0.70. Cost per solved task is known for neither of them.
Which has the bigger context window, Mercury 2 or Qwen3 VL 30B A3B Instruct?
Qwen3 VL 30B A3B Instruct, with 262K tokens against 128K.
How many benchmarks is the Mercury 2 vs Qwen3 VL 30B A3B Instruct comparison based on?
6 benchmarks have a result for both models as of October 22, 2026. Mercury 2's coding index rests on 1 independent benchmark and Qwen3 VL 30B A3B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.