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Qwen3.5 397B A17B

Qwentext + image + video → textHugging Face OpenRouter

The cheapest provider for Qwen3.5 397B A17B is Alibaba at $0.878 per 1M tokens (blended), charging $0.39 per 1M input and $2.34 per 1M output tokens. 10 providers serve it; the most expensive charges 1.92× as much. Context window: 256K tokens. Prices tracked since Oct 3, 2026.

Best price
$0.878
at Alibaba
Input / output
$0.39 / $2.34
per 1M tokens
Providers
10
1.92× spread
7 days
—
best price
30 days
—
best price
Context
256K
tokens

Providers

Active offers ranked by blended price. Bars are relative to the most expensive.

  • AlibabaCheapest
    $0.878
    $0.39 in · $2.34 out
    best
    256K ctx99.9% uptime
  • $1.09
    $0.45 in · $3.00 out
    +24%
    256K ctx98.3% uptimefp8
  • $1.275
    $0.50 in · $3.60 out
    +45%
    256K ctx99.9% uptimefp8
  • $1.29
    $0.55 in · $3.50 out
    +47%
    256K ctx97.3% uptimefp8
  • $1.29
    $0.55 in · $3.50 out
    +47%
    128K ctx94.4% uptime
  • $1.29
    $0.55 in · $3.50 out
    +47%
    256K ctx99.8% uptime
  • $1.35
    $0.60 in · $3.60 out
    +54%
    256K ctx95.7% uptimefp8
  • $1.35
    $0.60 in · $3.60 out
    +54%
    256K ctx91.4% uptime
  • $1.35
    $0.60 in · $3.60 out
    +54%
    250K ctx98.2% uptime
  • $1.69
    $0.75 in · $4.50 out
    +92%
    125K ctx98.4% uptime
Blended = (3 × input + output) / 4.

Price history

Hover to compare providers at any point in time. Click a legend item to hide it.

USD per 1M tokens · each step is a price change
Not enough history yet
Tracking since Oct 3, 2026. The chart fills in as new crawls arrive every 6 hours.

Other pricing

Cache, reasoning and per-call fees. Token rates per 1M; others per unit.

Offered byCache read
DeepInfra$0.22
Parasail$0.30
AtlasCloud$0.55
DigitalOcean$0.11
Phala$0.225
StreamLake$0.12

Change log

Every recorded change for this model since Oct 3, 2026.

No changes yet
Tracking since Oct 3, 2026. Price changes, new providers and delistings will show up here.

About this model

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...
Released
Feb 16, 2026
First tracked
Oct 3, 2026
Canonical slug
qwen/qwen3.5-397b-a17b-20260216
Weights
Qwen/Qwen3.5-397B-A17B