Qwen3.5-122B-A10B vs Fugu Ultra
Qwen3.5-122B-A10B costs 14.4x less per output token than Fugu Ultra ($2.08 vs $30.00 per million). Updated October 23, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $2.08
- Coding
- No data
- Overall
- No data
- Output $/M
- $30.00
Qwen3.5-122B-A10B or Fugu Ultra: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen3.5-122B-A10B for output tokens 14.4x cheaper ($2.08 vs $30.00 per million).
No benchmark has tested both yet. Qwen3.5-122B-A10B has results on LMArena WebDev, AA Coding Index and SciCode; Fugu Ultra 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 Qwen3.5-122B-A10B has a AA Intelligence Index result, 17.7.
Directional only
Long documents
Listed context window
Fugu Ultra
Fugu Ultra takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-122B-A10B
Qwen3.5-122B-A10B $0.0013, Fugu Ultra $0.020 per turn.
List prices
At a glance
- Coding index
- Qwen3.5-122B-A10B not benchmarked, Fugu Ultra 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
- Qwen3.5-122B-A10B $2.08 against Fugu Ultra $30.00 per million output tokens, 14.4x apart.
- Context window
- Qwen3.5-122B-A10B takes 262K tokens, Fugu Ultra 1M.
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 Index8 boards measured
| Benchmark | Qwen3.5-122B-A10B | Fugu Ultra | Leader |
|---|---|---|---|
| LMArena WebDev | 1361 | Not measured | Only Qwen3.5-122B-A10B measured |
| AA Coding Index | 43.3 | Not measured | Only Qwen3.5-122B-A10B measured |
| SciCode | 39.7% | Not measured | Only Qwen3.5-122B-A10B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 31.1% | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: coding | 1436 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: software and IT | 1436 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena WebDev: React | 1352 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena WebDev: HTML | 1352 | Not measured | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen3.5-122B-A10B | Fugu Ultra | Leader |
|---|---|---|---|
| AA Intelligence Index | 17.7 | Not measured | Only Qwen3.5-122B-A10B 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 | Qwen3.5-122B-A10B | Fugu Ultra | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 93.6% | Not measured | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Qwen3.5-122B-A10B | Fugu Ultra | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 85.7% | Not measured | Only Qwen3.5-122B-A10B measured |
| Humanity's Last Exam (Artificial Analysis run) | 25.2% | Not measured | Only Qwen3.5-122B-A10B measured |
| Mystery game puzzles | 17.0% | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: hard prompts | 1421 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: expert | 1431 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: hard prompts in English | 1431 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: diagrams | 1249 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: homework | 1261 | Not measured | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen3.5-122B-A10B | Fugu Ultra | Leader |
|---|---|---|---|
| LMArena Text: math | 1431 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: mathematical work | 1431 | Not measured | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Qwen3.5-122B-A10B | Fugu Ultra | Leader |
|---|---|---|---|
| LMArena Text: science | 1433 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: medicine and healthcare | 1423 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: legal and government | 1422 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: business and finance | 1414 | Not measured | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 16 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index27 boards measured
| Benchmark | Qwen3.5-122B-A10B | Fugu Ultra | Leader |
|---|---|---|---|
| IFBench | 75.7% | Not measured | Only Qwen3.5-122B-A10B measured |
| Long context reasoning (AA-LCR) | 76.3% | Not measured | Only Qwen3.5-122B-A10B measured |
| DTBench | 84.3% | Not measured | Only Qwen3.5-122B-A10B measured |
| LMCA | 32.2% | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text | 1418 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: instruction following | 1400 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: creative writing | 1368 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Vision | 1244 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: English | 1428 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: non-English | 1401 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Chinese | 1463 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: German | 1425 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Japanese | 1367 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Korean | 1353 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: French | 1443 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Spanish | 1425 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Russian | 1400 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: Polish | 1399 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: multi-turn | 1417 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: longer queries | 1411 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: writing and language | 1387 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: entertainment and media | 1366 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: English | 1249 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: Chinese | 1301 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: reading text | 1251 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: humor | 1243 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: creative writing | 1220 | Not measured | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 21 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
Qwen3.5-122B-A10B costs less
Repository review
50K input + 3K output tokens
Qwen3.5-122B-A10B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-122B-A10B 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 | Qwen3.5-122B-A10B | Sakana Fugu Ultra |
|---|---|---|
| Maker | Qwen | Sakana |
| Weights | Open weights | No public weights listed |
| Released | February 25, 2026 | June 24, 2026 |
| Context window | 262K | 1M |
| Input $/Mtok | $0.26 | $5.00 |
| Output $/Mtok | $2.08 | $30.00 |
| 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 Qwen3.5-122B-A10B better than Fugu Ultra for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen3.5-122B-A10B for output tokens 14.4x cheaper ($2.08 vs $30.00 per million).
Which is cheaper, Qwen3.5-122B-A10B or Fugu Ultra?
Qwen3.5-122B-A10B costs $0.26 per million input tokens and $2.08 per million output tokens; Fugu Ultra costs $5.00 and $30.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen3.5-122B-A10B or Fugu Ultra?
Fugu Ultra, with 1M tokens against 262K.
Has any benchmark tested both Qwen3.5-122B-A10B and Fugu Ultra?
No benchmark has tested both yet. Qwen3.5-122B-A10B has results on LMArena WebDev, AA Coding Index and SciCode; Fugu Ultra has none yet. Compare them on price and context instead. Data as of October 23, 2026.