Qwen3.8 Flash

AlibabaKey qwen3.8-flashAlso reported as ali/qwen3.8-flash, b-ai/qwen3.8-flash, qwen/qwen3.8-flash, ses-lite/qwen3.8-flash, bai/qwen3.8-flash, opencode-go/qwen3.8-flash

Rank
#70
by active users
Active users
18
Down 7 from 25 active users in the previous 30 days. vs previous 30 days
Adoption
1.9%
of 958 accounts
Tokens
6.9B
cache included
Est. cost
$11
at public list prices
First seen
Aug 27, 2026
in any submission

Oct 14 – Nov 12, 2026 (UTC)958 accounts100% of tokens from an identified modelData through Nov 12, 2026, 00:47 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 Qwen3.8 Flash, Oct 14, 2026 to Nov 12, 2026. Peak 6. Use the left and right arrow keys to read each day.630
Show daily values
Daily active users and tokens for Qwen3.8 Flash
Date (UTC)Active usersTokens
Oct 14, 202633.7M
Oct 15, 202638.3M
Oct 16, 20266185.1M
Oct 17, 20262558K
Oct 18, 202621.2M
Oct 19, 20263208.7M
Oct 20, 20264274.2M
Oct 21, 2026245.2M
Oct 22, 20261143.5M
Oct 23, 20261354.3M
Oct 24, 20262674.4M
Oct 25, 20262781.6M
Oct 26, 20261185.9M
Oct 27, 202615.8M
Oct 28, 202612.6M
Oct 29, 202600
Oct 30, 202600
Oct 31, 202600
Nov 1, 2026130.1K
Nov 2, 202600
Nov 3, 2026273.2M
Nov 4, 20264179.3M
Nov 5, 20263615.7M
Nov 6, 20261939.9M
Nov 7, 20262645.2M
Nov 8, 2026227.5M
Nov 9, 20262671M
Nov 10, 20261802M
Nov 11, 2026242.3M
Nov 12, 202600

Token mix

How the 6.9B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.

  • Input3.5%
  • Output0.3%
  • Cache read95%
  • Cache write0.3%
  • Reasoning0.5%

Agents that carry Qwen3.8 Flash

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

  1. Hermes Agent77% of this model's tokens2active users
  2. Reasonix18% of this model's tokens1active users
  3. Claude Code3.4% of this model's tokens4active users
  4. Codex CLI1.2% of this model's tokens1active users
  5. OpenCode0.3% of this model's tokens6active users
  6. Pi<0.1% of this model's tokens1active users
  7. Oh My Pi<0.1% of this model's tokens4active users
  8. cc-mirror/python-urllib<0.1% of this model's tokens1active users
  9. cc-mirror/mozilla<0.1% of this model's tokens1active users
  10. cc-mirror/curl<0.1% of this model's tokens1active users

Benchmarks

The best result for Qwen3.8 Flash 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

No benchmark that Tokscale tracks has a result for Qwen3.8 Flash yet.

Pricing

List prices from models.dev in US dollars per 1M tokens, retrieved Oct 21, 2026. Alibaba is the lab's own API and the reference price for the estimates below.

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
$0.02
Est. per 1M tokens
95% cache reads
At the community mix
$0.02
Est. per 1M tokens
96% cache reads
3:1 input/output blend
$0.23
Per 1M tokens at list prices
No cache

Cache reads were 95% of Qwen3.8 Flash tokens in the last 30 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.

Assumptions

  • Alibaba list prices per 1M tokens: input $0.15, output $0.47, cache read $0.02, cache write $0.20.
  • This model's mix is its own input, output, cache and reasoning tokens in the last 30 days.
  • The community mix is the tokens of every identified model in the last 30 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.

List prices by provider

  • AlibabaReferenceqwen3.8-flash
    $0.15 input per 1M tokens$0.47 output per 1M tokens$0.02 cache read per 1M tokens$0.20 cache write per 1M tokens1M tokens of context
  • OpenRouterqwen/qwen3.8-flash
    $0.15 input per 1M tokens$0.47 output per 1M tokens$0.02 cache read per 1M tokensCache write not listed1M tokens of context
  • Vercel AI Gatewayalibaba/qwen3.8-flash
    $0.15 input per 1M tokens$0.47 output per 1M tokens$0.02 cache read per 1M tokens$0.20 cache write per 1M tokens991K tokens of context
  • Deep InfraQwen/Qwen3.8-Flash
    $0.11 input per 1M tokens$0.38 output per 1M tokens$0.01 cache read per 1M tokensCache write not listed1M tokens of context

Specs

From models.dev (MIT), retrieved Oct 21, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.

Context window
1M tokens
Max output
131K tokens
Input
Text, Image, Video
Output
Text
Knowledge cutoff
— not listed
Release date
Aug 26, 2026
Open weights
No
Reasoning
Yes
Tool calling
Yes

Top public profiles

Public profiles that used Qwen3.8 Flash most in this period, by tokens. Hidden accounts are never listed.

  1. 1Benjamin Hodgens@bhodgens5.3Btokens—est. cost16active daysno price · 16 active days
  2. 2Baptiste@BaptisteFaisy1.2Btokens<$1est. cost7active days<$1 est. cost · 7 active days
  3. 3wxs2026-source@wxs2026-source174.5Mtokens$7est. cost4active days$7 est. cost · 4 active days
  4. 412zrr23@12zrr2383.9Mtokens$2est. cost2active days$2 est. cost · 2 active days
  5. 5adolphrui-beep@adolphrui-beep40Mtokens$1est. cost1active days$1 est. cost · 1 active days
  6. 6John Owen Nixon@johnowennixon14.2Mtokens<$1est. cost1active days<$1 est. cost · 1 active days
  7. 7Michael Burr@CubityFirst12.3Mtokens<$1est. cost2active days<$1 est. cost · 2 active days
  8. 8Chiao@chiaox458.4Mtokens—est. cost7active daysno price · 7 active days
  9. 9ljd0919@ljd09198.1Mtokens<$1est. cost2active days<$1 est. cost · 2 active days
  10. 10_~_@hygkui5.2Mtokens—est. cost2active daysno price · 2 active days

More from Alibaba

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

  1. Qwen3.8 Max1.7% adoption16active users
  2. Qwen3.8 Flash Next0.6% adoption6active users
  3. Qwen3.8 27B0.6% adoption6active users
  4. Qwen3 Coder Next0.4% adoption4active users
  5. Qwen 3.8 27B0.3% adoption3active users
  6. Qwen3.7 Max0.3% adoption3active 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.

  • models.devSpecs and list prices per provider.MIT · Retrieved Oct 21, 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