Qwen3.5-9B vs Sakana Namazu
Qwen3.5-9B costs 26.7x less per output token than Sakana Namazu ($0.15 vs $4.00 per million). Updated October 23, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
- Coding
- No data
- Overall
- No data
- Output $/M
- $4.00
Qwen3.5-9B or Sakana Namazu: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen3.5-9B for output tokens 26.7x cheaper ($0.15 vs $4.00 per million).
No benchmark has tested both yet. Qwen3.5-9B has results on AA Coding Index, SciCode and Terminal-Bench Hard (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 Qwen3.5-9B has a AA Intelligence Index result, 13.3.
Directional only
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-9B
Qwen3.5-9B $0.0002, Sakana Namazu $0.0029 per turn.
List prices
At a glance
- Coding index
- Qwen3.5-9B 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
- Qwen3.5-9B $0.15 against Sakana Namazu $4.00 per million output tokens, 26.7x 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 | Qwen3.5-9B | Sakana Namazu | Leader |
|---|---|---|---|
| AA Coding Index | 23.5 | Not measured | Only Qwen3.5-9B measured |
| SciCode | 29.5% | Not measured | Only Qwen3.5-9B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 24.2% | Not measured | Only Qwen3.5-9B measured |
| Terminal-Bench | 9.2% | Not measured | Only Qwen3.5-9B measured |
| Neither model has a result on the other 39 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen3.5-9B | Sakana Namazu | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.3 | Not measured | Only Qwen3.5-9B measured |
| Epoch Capabilities Index | 139.3 | Not measured | Only Qwen3.5-9B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen3.5-9B | Sakana Namazu | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 86.8% | Not measured | Only Qwen3.5-9B measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Qwen3.5-9B | Sakana Namazu | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 80.6% | Not measured | Only Qwen3.5-9B measured |
| Humanity's Last Exam (Artificial Analysis run) | 14.9% | Not measured | Only Qwen3.5-9B measured |
| GPQA Diamond (Epoch AI run) | 79.0% | Not measured | Only Qwen3.5-9B measured |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen3.5-9B | Sakana Namazu | Leader |
|---|---|---|---|
| OTIS Mock AIME | 61.7% | Not measured | Only Qwen3.5-9B measured |
| MathArena | 13.0% | Not measured | Only Qwen3.5-9B measured |
| Neither model has a result on the other 12 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Qwen3.5-9B | Sakana Namazu | Leader |
|---|---|---|---|
| IFBench | 66.7% | Not measured | Only Qwen3.5-9B measured |
| Long context reasoning (AA-LCR) | 70.0% | Not measured | Only Qwen3.5-9B measured |
| DTBench | 71.2% | Not measured | Only Qwen3.5-9B measured |
| LMCA | 24.5% | Not measured | Only Qwen3.5-9B measured |
| Neither model has a result on the other 44 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
Qwen3.5-9B costs less
Repository review
50K input + 3K output tokens
Qwen3.5-9B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-9B 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 | Qwen3.5-9B | Sakana Namazu |
|---|---|---|
| Maker | Qwen | Sakana |
| Weights | Open weights | No public weights listed |
| Released | March 10, 2026 | August 11, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.10 | $0.95 |
| Output $/Mtok | $0.15 | $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 Qwen3.5-9B better than Sakana Namazu for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen3.5-9B for output tokens 26.7x cheaper ($0.15 vs $4.00 per million).
Which is cheaper, Qwen3.5-9B or Sakana Namazu?
Qwen3.5-9B costs $0.10 per million input tokens and $0.15 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, Qwen3.5-9B or Sakana Namazu?
Neither: both take 262K tokens.
Has any benchmark tested both Qwen3.5-9B and Sakana Namazu?
No benchmark has tested both yet. Qwen3.5-9B has results on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run); Sakana Namazu has none yet. Compare them on price and context instead. Data as of October 23, 2026.