Qwen3 Coder 30B A3B Instruct vs Sakana Namazu
Qwen3 Coder 30B A3B Instruct costs 9.1x less per output token than Sakana Namazu ($0.44 vs $4.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.44
- Coding
- No data
- Overall
- No data
- Output $/M
- $4.00
Qwen3 Coder 30B A3B Instruct or Sakana Namazu: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen3 Coder 30B A3B Instruct for output tokens 9.1x cheaper ($0.44 vs $4.00 per million).
No benchmark has tested both yet. Qwen3 Coder 30B A3B Instruct has results on SWE-bench Verified, SWE-bench Lite and LiveCodeBench (Artificial Analysis run); Sakana Namazu has none yet. Compare them on price and context instead.
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
No call
Only Qwen3 Coder 30B A3B Instruct has a AA Intelligence Index result, 9.6.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3 Coder 30B A3B Instruct has a Design Arena: websites result, 1087.
Directional only
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Coder 30B A3B Instruct
Qwen3 Coder 30B A3B Instruct $0.0003, Sakana Namazu $0.0029 per turn.
List prices
At a glance
- Coding index
- Qwen3 Coder 30B A3B Instruct not benchmarked, Sakana Namazu not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Qwen3 Coder 30B A3B Instruct $0.44 against Sakana Namazu $4.00 per million output tokens, 9.1x apart.
- Context window
- Both take 262K tokens.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
| Benchmark | Qwen3 Coder 30B A3B Instruct | Sakana Namazu | Leader |
|---|---|---|---|
| SWE-bench Verified | 60.4% | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| SWE-bench Lite | 49.7% | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| LiveCodeBench (Artificial Analysis run) | 40.3% | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 39 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen3 Coder 30B A3B Instruct | Sakana Namazu | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.6 | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen3 Coder 30B A3B Instruct | Sakana Namazu | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 34.5% | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen3 Coder 30B A3B Instruct | Sakana Namazu | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 51.6% | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | 3.8% | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 21 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen3 Coder 30B A3B Instruct | Sakana Namazu | Leader |
|---|---|---|---|
| AA Math Index | 29.0 | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| AIME 2025 (Artificial Analysis run) | 29.0% | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen3 Coder 30B A3B Instruct | Sakana Namazu | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 70.6% | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 19 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Qwen3 Coder 30B A3B Instruct | Sakana Namazu | Leader |
|---|---|---|---|
| Design Arena: websites | 1087 | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Design Arena: UI components | 1044 | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Design Arena: data viz | 1085 | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 6 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen3 Coder 30B A3B Instruct | Sakana Namazu | Leader |
|---|---|---|---|
| IFBench | 32.7% | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Long context reasoning (AA-LCR) | 32.7% | Not measured | Only Qwen3 Coder 30B A3B Instruct measured |
| Neither model has a result on the other 46 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 Coder 30B A3B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen3 Coder 30B A3B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen3 Coder 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 | Qwen3 Coder 30B A3B Instruct | Sakana Namazu |
|---|---|---|
| Maker | Qwen | Sakana |
| Weights | Open weights | No public weights listed |
| Released | July 31, 2025 | August 11, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.11 | $0.95 |
| Output $/Mtok | $0.44 | $4.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3 Coder 30B A3B Instruct better than Sakana Namazu for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen3 Coder 30B A3B Instruct for output tokens 9.1x cheaper ($0.44 vs $4.00 per million).
Which is cheaper, Qwen3 Coder 30B A3B Instruct or Sakana Namazu?
Qwen3 Coder 30B A3B Instruct costs $0.11 per million input tokens and $0.44 per million output tokens; Sakana Namazu costs $0.95 and $4.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen3 Coder 30B A3B Instruct or Sakana Namazu?
Neither: both take 262K tokens.
Has any benchmark tested both Qwen3 Coder 30B A3B Instruct and Sakana Namazu?
No benchmark has tested both yet. Qwen3 Coder 30B A3B Instruct has results on SWE-bench Verified, SWE-bench Lite and LiveCodeBench (Artificial Analysis run); Sakana Namazu has none yet. Compare them on price and context instead. Data as of October 22, 2026.