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Model

qwen3.5-9b

qwen3.5-9b from Together AI, Fast class. List prices per million tokens, and what the public benchmarks say about it.

Class
Fast
Input, per million
$0.17
Output, per million
$0.25
Cached input
$0.00
Context window
262,144
Longest answer
262,144
Processed in
global
Prices from
23 September 2026

Calling it

Name it in the model field, or let auto choose it for you.

"model": "qwen3.5-9b"

Supports: images, tools, JSON schema

auto can pick this model when it suits the job and the line you chose.

What it costs

  • Input $0.17 and output $0.25 per million tokens, at the provider list price.
  • Input read from cache: $0.00 per million tokens.

Public results for this model

Zabio has not run its own tests on this model. Everything below is aggregated from public benchmarks, with the sources named.

Aggregated from public resultsRead on 1 October 2026

qwen3.5-9b
Analysis and reasoning, Hard: 79.0 +/- 2.4 Evidence, in standard errors: 0.3 GPQA diamond: 79.0 (Same settings as ours)Analysis and reasoning, Hard79.0Math, Hardest: 42.8 +/- 6.5 Evidence, in standard errors: -1.0 OTIS Mock AIME 2024-2025: 42.8 (Same settings as ours)Math, Hardest42.8Fixing code, Hard: 9.2 +/- 2.4 Evidence, in standard errors: -3.4 Terminal Bench: 9.2 (Same settings as ours)Fixing code, Hard9.2Using tools, Hard: 9.2 +/- 2.4 Evidence, in standard errors: -2.5 Terminal Bench: 9.2 (Same settings as ours)Using tools, Hard9.2
The benchmarks behind each bar
Kind of jobBenchmarkScoreSettings
Analysis and reasoning, HardGPQA diamond79.0Same settings as ours
Math, HardestOTIS Mock AIME 2024-202542.8Same settings as ours
Fixing code, HardTerminal Bench9.2Same settings as ours
Using tools, HardTerminal Bench9.2Same settings as ours
Price against score in each kind of job (4)

Price per 1,000 tasks, USD. Score, %. Greyed out: a cheaper model already scores as well. Ringed: the best, balanced and cheap choice.

Analysis and reasoning, Hard
0255075100$1$10$100 qwen3.5-9b: 79.0 +/- 2.4, $0.57 gpt-oss-120b: 75.8 +/- 2.7, $0.84 mistral-small-2603: 47.5 +/- 2.8, $0.84 gpt-4o-mini: 37.7 +/- 2.4, $0.84 gpt-5.4-nano: 66.1 +/- 2.4, $1.53 deepseek-flash: 79.0 +/- 2.0, $1.68 deepseek-flash@together: 79.0 +/- 2.0, $1.68 gpt-4.1-mini: 65.9 +/- 2.7, $2.24 gpt-5-mini: 71.7 +/- 3.2, $2.30 mistral-large-2512: 51.3 +/- 2.7, $2.35 gemini-3.5-flash-lite: 68.7 +/- 2.3, $2.85 llama-3.3-70b-instruct-turbo: 47.4 +/- 2.9, $3.02 gemini-3.8-flash: 92.3 +/- 1.3, $4.88 gpt-5.4-mini: 67.1 +/- 2.4, $5.55 deepseek-v4-pro: 78.0 +/- 2.1, $6.20 deepseek-v4-pro@together: 78.0 +/- 2.1, $6.20 claude-haiku-4-5: 60.5 +/- 2.8, $6.50 mistral-medium-3-5: 59.5 +/- 2.8, $9.75 grok-4.7: 82.7 +/- 2.7, $10.34 gemini-3.5-flash: 85.8 +/- 1.7, $11.10 gpt-4.1: 66.9 +/- 2.8, $11.20 claude-sonnet-5: 84.5 +/- 1.8, $13.00 gemini-3.1-pro-preview: 89.5 +/- 1.5, $14.80 gpt-5.4: 80.3 +/- 2.1, $18.50 claude-sonnet-4-6: 81.8 +/- 1.9, $19.50 claude-opus-5-5: 91.4 +/- 1.4, $26.00 claude-opus-5: 92.2 +/- 1.4, $32.50 claude-opus-4-8: 86.9 +/- 1.7, $32.50 gpt-5.5: 82.4 +/- 2.0, $37.00 gpt-6-astra: 94.2 +/- 1.2, $65.00 claude-fable-5-1: 91.7 +/- 1.9, $65.00 qwen3.5-9bgemini-3.8-flash Cheapclaude-opus-5-5 Best, Balanced
Math, Hardest
0255075100$1$10$100 qwen3.5-9b: 42.8 +/- 6.5, $0.89 gpt-oss-120b: 88.9 +/- 4.5, $1.35 mistral-small-2603: 5.3 +/- 2.6, $1.35 gpt-4o-mini: 3.8 +/- 1.4, $1.35 gpt-5.4-nano: 25.7 +/- 2.9, $2.48 deepseek-flash: 76.0 +/- 1.8, $2.70 deepseek-flash@together: 76.0 +/- 1.8, $2.70 gpt-4.1-mini: 18.6 +/- 2.2, $3.60 gpt-5-mini: 34.1 +/- 2.9, $3.75 mistral-large-2512: 1.1 +/- 0.5, $3.75 gemini-3.5-flash-lite: 44.6 +/- 4.2, $4.65 llama-3.3-70b-instruct-turbo: 5.1 +/- 2.4, $4.68 gemini-3.8-flash: 83.7 +/- 1.5, $7.88 gpt-5.4-mini: 23.6 +/- 2.7, $9.00 deepseek-v4-pro: 54.0 +/- 4.6, $9.90 deepseek-v4-pro@together: 54.0 +/- 4.6, $9.90 claude-haiku-4-5: 20.0 +/- 3.2, $10.50 mistral-medium-3-5: 16.3 +/- 3.0, $15.75 gemini-3.5-flash: 65.3 +/- 2.2, $18.00 gpt-4.1: 16.6 +/- 2.2, $18.00 claude-sonnet-5: 72.8 +/- 3.3, $21.00 gemini-3.1-pro-preview: 64.1 +/- 1.7, $24.00 gpt-5.4: 60.9 +/- 3.3, $30.00 claude-sonnet-4-6: 51.8 +/- 3.7, $31.50 claude-opus-5-5: 95.6 +/- 2.6, $42.00 claude-opus-5: 92.8 +/- 1.6, $52.50 claude-opus-4-8: 72.3 +/- 2.5, $52.50 gpt-5.5: 69.1 +/- 4.5, $60.00 gpt-6-astra: 96.8 +/- 2.6, $105 claude-fable-5-1: 95.1 +/- 2.7, $105 qwen3.5-9bgpt-oss-120b Cheapdeepseek-flash Balancedclaude-opus-5-5 Best
Fixing code, Hard
0255075100$1$10$100 qwen3.5-9b: 9.2 +/- 2.4, $0.68 gpt-oss-120b: 25.6 +/- 1.9, $1.11 gpt-4o-mini: 3.6 +/- 1.2, $1.11 codestral-2508: 11.1 +/- 2.1, $1.82 gpt-5.4-nano: 46.8 +/- 5.9, $2.09 deepseek-flash: 37.6 +/- 5.7, $2.22 deepseek-flash@together: 37.6 +/- 5.7, $2.22 gpt-4.1-mini: 32.4 +/- 3.1, $2.96 gpt-5-mini: 47.0 +/- 1.7, $3.20 gemini-3.5-flash-lite: 45.3 +/- 5.9, $3.98 gemini-3.8-flash: 54.2 +/- 5.9, $6.56 gpt-5.4-mini: 41.7 +/- 5.8, $7.58 deepseek-v4-pro: 57.1 +/- 3.5, $7.99 deepseek-v4-pro@together: 57.1 +/- 3.5, $7.99 claude-haiku-4-5: 13.9 +/- 2.7, $8.75 grok-4.7: 54.0 +/- 5.9, $13.31 gpt-4.1: 49.8 +/- 1.9, $14.80 gemini-3.5-flash: 64.2 +/- 3.1, $15.15 claude-sonnet-5: 59.4 +/- 5.8, $17.50 gemini-3.1-pro-preview: 49.8 +/- 4.0, $20.20 gpt-5.4: 69.7 +/- 2.3, $25.25 claude-sonnet-4-6: 59.9 +/- 2.2, $26.25 claude-opus-5-5: 71.7 +/- 5.3, $35.00 claude-opus-5: 65.2 +/- 5.6, $43.75 claude-opus-4-8: 50.5 +/- 5.9, $43.75 gpt-5.5: 59.0 +/- 3.6, $50.50 claude-fable-5-1: 66.1 +/- 5.6, $87.50 gpt-6-astra: 57.3 +/- 5.8, $87.50 qwen3.5-9bclaude-sonnet-5 Cheapclaude-opus-5-5 Best, Balanced
Using tools, Hard
0255075100$1$10$100 qwen3.5-9b: 9.2 +/- 2.4, $1.13 gpt-oss-120b: 14.2 +/- 2.3, $1.68 gpt-5-mini: 22.3 +/- 2.6, $4.60 claude-haiku-4-5: 13.9 +/- 2.7, $13.00 gemini-3.1-pro-preview: 59.4 +/- 4.2, $29.60 gpt-5.4: 81.8 +/- 2.0, $37.00 claude-sonnet-4-6: 62.8 +/- 1.8, $39.00 gpt-5.5: 66.1 +/- 2.5, $74.00 qwen3.5-9bgpt-5.4 Best, Balanced, Cheap

Sources

  • Epoch AIEpoch AI, Capabilities and Benchmarking, epoch.ai/benchmarks, retrieved 2026-10-01License: CC BY 4.0Read on 1 October 2026

What these numbers are

  • These numbers come from the sources named on each row, not from Zabio's own tests. Zabio's tests are shown separately and never combined with them into one figure.
  • Sources test models at their own settings. A settings mismatch against how Zabio calls the model is marked on the row and lowers its weight.
  • Scores are compared only inside one benchmark. Task scores combine benchmarks by evidence in standard errors, so a task score is a summary, not a benchmark result.
  • A model missing from every source is listed as such rather than left out.

Results from our own tests have their own section.

Where to next

How routing picks between these models

Model and company names are trademarks of their owners. Zabio uses these models through their vendors' APIs and is not affiliated with the vendors.