Qwen3.5 9B

AlibabaKey qwen3.5-9bAlso reported as qwen3.5:9b, qwen/qwen3.5-9b, unsloth/qwen3.5-9b, lmstudio-community/qwen3.5-9b

Rank
#220
by active users
Active users
1
Down 1 from 2 active users in the previous 7 days. vs previous 7 days
Adoption
0.2%
of 610 accounts
Tokens
25.5M
cache included
Est. cost
—
at public list prices
First seen
Mar 2, 2026
in any submission

Nov 6–12, 2026 (UTC)610 accounts100% of tokens from an identified modelData through Nov 12, 2026, 08:13 UTCHow we count

Daily active users

Distinct accounts that used this model on each UTC day.

0 active users on Nov 12, 2026

Daily active users for Qwen3.5 9B, Nov 6, 2026 to Nov 12, 2026. Peak 1. Use the left and right arrow keys to read each day.110
Show daily values
Daily active users and tokens for Qwen3.5 9B
Date (UTC)Active usersTokens
Nov 6, 2026125.5M
Nov 7, 202600
Nov 8, 202600
Nov 9, 202600
Nov 10, 202600
Nov 11, 202600
Nov 12, 202600

Token mix

How the 25.5M tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.

  • Input97%
  • Output2.6%
  • Cache read0%
  • Cache write0%
  • Reasoning0%

Agents that carry Qwen3.5 9B

Each agent's share of this model's tokens, and how many accounts used the model through it.

  1. LM Studio100% of this model's tokens1active users

Benchmarks

The best result for Qwen3.5 9B in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark.

All benchmarks
  • Epoch Capabilities IndexOverall · Epoch AI
    139.3
    Rank #119 of 158 matched modelsNo conditions reportedModel released Feb 24, 2026Source: epoch.ai (opens in a new tab)
  • GPQA DiamondReasoning · Epoch AI
    79.0%
    Rank #93 of 160 matched modelsNo conditions reportedRun date Aug 27, 2026Source: epoch.ai (opens in a new tab)

    Near its ceiling: the top score is 96.5%, and Epoch AI estimates the reachable maximum at 97%. Differences between top models are small.

    Show 1 more result with other run conditionsHide the other results
    • Listed as qwen3.5-9B_none
      78.9%
      No reasoningRun date Aug 27, 2026Source: epoch.ai (opens in a new tab)

Not evaluated: Humanity's Last Exam, FrontierMath Tiers 1–3 (v2), SimpleQA Verified, Terminal-Bench 4.1, CursorBench, DeepSWE, FrontierSWE, Agent Arena, WebDev Arena. A missing result is not a score of zero.

Pricing

List prices from models.dev in US dollars per 1M tokens, retrieved Nov 12, 2026. OpenRouter is the reference price for the estimates below. It is the first provider listed; models.dev lists no price from the lab's own API.

Price at real agent usageEstimate at list prices

What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.

At this model's mix
$0.16
Est. per 1M tokens
0% cache reads
At the community mix
$0.14
Est. per 1M tokens
96% cache reads
3:1 input/output blend
$0.18
Per 1M tokens at list prices
No cache

Cache reads were 0% of Qwen3.5 9B tokens in the last 7 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.

Assumptions

  • OpenRouter list prices per 1M tokens: input $0.16, output $0.23, cache read $0.14.
  • This model's mix is its own input, output, cache and reasoning tokens in the last 7 days.
  • The community mix is the tokens of every identified model in the last 7 days.
  • This is an estimate at list prices, not what anyone paid.
  • Reasoning tokens are priced as output.
  • Long-context tiers, batch pricing and discounts are not applied.
  • Token mixes come from public Tokscale submissions. Hidden accounts are excluded.
  • No cache-write price is listed, so cache writes are priced as input.

List prices by provider

  • OpenRouterReferenceqwen/qwen3.5-9b
    $0.16 input per 1M tokens$0.23 output per 1M tokens$0.14 cache read per 1M tokensCache write not listed262K tokens of context
  • Together AIQwen/Qwen3.5-9B
    $0.17 input per 1M tokens$0.25 output per 1M tokensCache read not listedCache write not listed262K tokens of context
  • Deep InfraQwen/Qwen3.5-9B
    $0.10 input per 1M tokens$0.15 output per 1M tokensCache read not listedCache write not listed262K tokens of context

Specs

From models.dev (MIT), retrieved Nov 12, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.

Context window
262K tokens
Max output
66K tokens
Input
Text, Image, Video
Output
Text
Knowledge cutoff
— not listed
Release date
Feb 23, 2026
Open weights
Yes
Reasoning
Yes
Tool calling
Yes

Top public profiles

Public profiles that used Qwen3.5 9B most in this period, by tokens. Hidden accounts are never listed.

  1. 1Minjun Kim (Lapis0875)@Lapis087525.5Mtokens—est. cost1active daysno price · 1 active days

More from Alibaba

Other Alibaba models in the same period, by active users.

  1. Qwen3.8 Flash0.8% adoption5active users
  2. Qwen3.8 Max0.5% adoption3active users
  3. Qwen4 Max Preview0.3% adoption2active users
  4. Qwen3 Coder Next0.3% adoption2active users
  5. Qwen3.8 Flash Next Iq3_s0.2% adoption1active users
  6. Qwen38 XHigh Assistant0.2% adoption1active users
All models

Sources and attribution

Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.

  • Epoch AIEpoch Capabilities Index, Epoch's own runs and the external results it collects.CC BY 4.0 · Retrieved Nov 12, 2026 · Data through Nov 9, 2026Epoch AI, ‘Capabilities & benchmarking’. Published online at epoch.ai. Retrieved from https://epoch.ai/benchmarks.
  • models.devSpecs and list prices per provider.MIT · Retrieved Nov 12, 2026models.dev, an open catalog of AI models (github.com/anomalyco/models.dev).
  • TokscaleActive users, tokens and token mix from public Tokscale submissions. Hidden accounts are excluded.How we count