Qwen3.8 Max

AlibabaKey qwen3.8-maxAlso reported as alibaba/qwen3.8-max, qwen/qwen3.8-max, alibaba-token-plan-intl/qwen3.8-max, ali/qwen3.8-max, alibaba-token/qwen3.8-max, cline-pass/qwen3.8-max, modelstudio/qwen3.8-max, gk/gk/qwen3.8-max, qwen-cloud/qwen3.8-max, opencode-go/qwen3.8-max, th/qwen3.8-max, qwen-token-plan/qwen3.8-max, cp/cline-pass/qwen3.8-max, go/qwen3.8-max, ocg/qwen3.8-max, gk/qwen3.8-max

Rank
#79
by active users
Active users
16
Down 8 from 24 active users in the previous 30 days. vs previous 30 days
Adoption
1.7%
of 958 accounts
Tokens
6.2B
cache included
Est. cost
$462
at public list prices
First seen
Jul 20, 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 Max, Oct 14, 2026 to Nov 12, 2026. Peak 5. Use the left and right arrow keys to read each day.530
Show daily values
Daily active users and tokens for Qwen3.8 Max
Date (UTC)Active usersTokens
Oct 14, 20265104M
Oct 15, 20264385.7M
Oct 16, 20263470.1M
Oct 17, 20262239.8M
Oct 18, 2026437.3M
Oct 19, 20262987.9M
Oct 20, 20262551.5M
Oct 21, 20263713.3M
Oct 22, 20262981M
Oct 23, 2026117.1M
Oct 24, 2026153.3M
Oct 25, 20262194.1M
Oct 26, 20264525.3M
Oct 27, 2026340.2M
Oct 28, 2026224.9M
Oct 29, 2026136.4M
Oct 30, 20263303.3M
Oct 31, 20262148.7M
Nov 1, 2026254.3M
Nov 2, 20262127M
Nov 3, 2026333.9M
Nov 4, 2026593M
Nov 5, 2026458M
Nov 6, 202600
Nov 7, 202600
Nov 8, 20261270
Nov 9, 202600
Nov 10, 202611.8M
Nov 11, 202600
Nov 12, 202600

Token mix

How the 6.2B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.

  • Input2.3%
  • Output0.3%
  • Cache read97%
  • Cache write<0.1%
  • Reasoning0.3%

Agents that carry Qwen3.8 Max

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

  1. Codex CLI51% of this model's tokens2active users
  2. Hermes Agent38% of this model's tokens2active users
  3. Gajae Code5.1% of this model's tokens1active users
  4. Claude Code2.2% of this model's tokens5active users
  5. Senpi (OmO Native)2.0% of this model's tokens1active users
  6. OpenClaw0.9% of this model's tokens2active users
  7. OpenCode0.8% of this model's tokens3active users
  8. Oh My Pi<0.1% of this model's tokens2active 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 Max 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
    157.4
    Rank #21 of 160 matched modelsNo conditions reportedModel released Aug 2, 2026Source: epoch.ai (opens in a new tab)
  • DeepSWEAgentic coding · Datacurve, collected by Epoch AI
    57.5%
    Rank #15 of 26 matched modelsXHigh · mini-swe-agentModel released Aug 2, 2026Source: deepswe.datacurve.ai (opens in a new tab)
  • FrontierSWEAgentic coding · FrontierSWE, collected by Epoch AI
    15.8%
    Rank #19 of 21 matched modelsXHigh · proximusModel released Aug 2, 2026Source: frontierswe.com (opens in a new tab)
  • WebDev ArenaWeb development · LMArena
    1,672
    Rank #11 of 110 matched modelsNo conditions reportedPublished Oct 19, 2026Source: huggingface.co (opens in a new tab)
  • Agent ArenaAgents · LMArena
    +0.02
    Rank #24 of 48 matched modelsArena Agent ModePublished Oct 19, 2026Source: huggingface.co (opens in a new tab)
  • GPQA DiamondReasoning · Epoch AI
    92.7%
    Rank #22 of 151 matched modelsXHighRun date Aug 4, 2026Source: epoch.ai (opens in a new tab)

    Near its ceiling: the top score is 96.4%, and Epoch AI estimates the reachable maximum at 97%. Differences between top models are small.

  • FrontierMath Tiers 1–3 (v2)Reasoning · Epoch AI
    74.7%
    Rank #21 of 86 matched modelsXHighRun date Aug 4, 2026Source: epoch.ai (opens in a new tab)

    Near its ceiling: the top score is 93.7%, and Epoch AI estimates the reachable maximum at 95%. Differences between top models are small.

  • SimpleQA VerifiedKnowledge · Epoch AI
    45.8%
    Rank #38 of 80 matched modelsXHighRun date Aug 27, 2026Source: epoch.ai (opens in a new tab)

Not evaluated: Humanity's Last Exam, Terminal-Bench 4.0, CursorBench. A missing result is not a score of zero.

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
$0.33
Est. per 1M tokens
97% cache reads
At the community mix
$0.34
Est. per 1M tokens
96% cache reads
3:1 input/output blend
$3
Per 1M tokens at list prices
No cache

Cache reads were 97% of Qwen3.8 Max 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 $2, output $6, cache read $0.25, cache write $2.50.
  • 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-max
    $2 input per 1M tokens$6 output per 1M tokens$0.25 cache read per 1M tokens$2.50 cache write per 1M tokens1M tokens of context
  • Fireworks AIaccounts/fireworks/models/qwen3p8-max
    $2 input per 1M tokens$6 output per 1M tokens$0.25 cache read per 1M tokensCache write not listed262K tokens of context
  • Deep InfraQwen/Qwen3.8-Max
    $1.65 input per 1M tokens$4.95 output per 1M tokens$0.21 cache read per 1M tokensCache write not listed256K 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, PDF
Output
Text
Knowledge cutoff
— not listed
Release date
Aug 3, 2026
Open weights
No
Reasoning
Yes
Tool calling
Yes

Top public profiles

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

  1. 1Chiao@chiaox453.2Btokens$437est. cost10active days$437 est. cost · 10 active days
  2. 2Benjamin Hodgens@bhodgens2.3Btokens—est. cost18active daysno price · 18 active days
  3. 3Hoyuo@Hoyuo444.2Mtokens—est. cost9active daysno price · 9 active days
  4. 4adolphrui-beep@adolphrui-beep61.5Mtokens—est. cost3active daysno price · 3 active days
  5. 5chickenWu@Gerson-57748.6Mtokens$25est. cost3active days$25 est. cost · 3 active days
  6. 6Christopher Butler@techsaint47.7Mtokens—est. cost3active daysno price · 3 active days
  7. 7Junho Yeo@junhoyeo29.8Mtokens—est. cost4active daysno price · 4 active days
  8. 8heyrm@rizlmaulanaa28.6Mtokens—est. cost2active daysno price · 2 active days
  9. 9ljd0919@ljd091914.9Mtokens—est. cost3active daysno price · 3 active days
  10. 10wxs2026-source@wxs2026-source13.6Mtokens—est. cost3active daysno price · 3 active days

More from Alibaba

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

  1. Qwen3.8 Flash1.9% adoption18active 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.

  • Epoch AIEpoch Capabilities Index, Epoch's own runs and the external results it collects.CC BY 4.0 · Retrieved Oct 21, 2026 · Data through Oct 15, 2026Epoch AI, ‘Capabilities & benchmarking’. Published online at epoch.ai. Retrieved from https://epoch.ai/benchmarks.
  • LMArenaWebDev Arena and Agent Arena leaderboards.CC BY 4.0 · Retrieved Oct 21, 2026 · Data through Oct 19, 2026LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), Hugging Face.
  • 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