Qwen3.8 Max API pricing
Alibaba's largest Qwen tier. Available at listed at platform rate (no published official USD price).
| Route | Input / 1M | Output / 1M |
|---|---|---|
| Platform rate | $1 | $3 |
USD, standard tier. Rate read from the live rate config on 2026-11-01. Alibaba publishes no USD list price for this model, so nothing here is cross-checked against one — this is a gateway rate, not a discount.
Specifications
| Vendor | Alibaba |
| Context window | — |
| Max output | — |
| Category | China |
What Qwen3.8 Max costs at your volume
| Usage level | Input / output per month | Monthly cost |
|---|---|---|
| Light (prototyping), a few thousand calls | 5M / 1M | $8.00 |
| Working, one developer, daily use | 50M / 10M | $80.00 |
| Heavy — team or agent loops in production | 500M / 100M | $800.00 |
Calculated at $1 input / $3 output per 1M tokens, 3.0× apart on this model, assuming a 5:1 input-to-output ratio. That ratio is the single largest source of error in this table: resend-heavy workloads drift well past it, and at 3.0× the correction is not linear. The cost calculator takes the actual figures.
When Qwen3.8 Max is the right call
At $1 in and $3 out per million tokens, Qwen3.8 Max lands where most production deployments actually live — cheap enough to leave running, expensive enough that you still look at the bill. The 3.0× output multiple is conventional, so standard cost intuition holds: output dominates, context matters, neither is pathological.
It is not the answer at either end. Bulk classification finds identical results several times cheaper, and the hardest reasoning problems reward moving up rather than staying here. Everything in between is this model's ground.
Where Qwen3.8 Max sits in the index
Qwen3.8 Max is 151 of 226 on input rate and 144 of 226 on output rate. A gap of 7 places, because on this model the output rate is 3.0× the input rate, flatter than the index median of 4.0× An output-heavy workload therefore leaves it almost where it started, which is why the cheapest model per input token is routinely not the cheapest per task. Percentile is the share of the 226 models in this index that cost more than Qwen3.8 Max.
| Ranked by | Position | Percentile | Rate |
|---|---|---|---|
| Input rate | 151 of 226 | 33% | $1.00 |
| Output rate | 144 of 226 | 36% | $3.00 |
| Agent mix 1:3, blended | 145 of 226 | 36% | $2.5 |
On an agent mix the lowest blended rate in the same index is Gemma2 9B It at $0.01 per 1M tokens, about 250.0× less than this model at the same ratio. Across the whole index, sorting by input price alone moves a model by as much as 74 places; on Qwen3.8 Max specifically the shift is 7 — which is what the re-ranked index exists to show.
Qwen3.8 Max is 151 of 226 across every model in the index; the comparison that usually settles a choice is Alibaba's own lineup further down.
Qwen3.8 Max among the 10 China-family models
Qwen3.8 Max is the 8th cheapest of the 10 China-family models in this index at $1 per 1M input tokens. The range inside that group runs from MiniMax M3.1 Flash at $0.075 to Kimi K3 at $1.5 (a spread of 20×, and this one sits at 13).3× the group's cheapest tier.
| Model | In / 1M | Out / 1M | vs this |
|---|---|---|---|
| MiniMax M3.1 Flash | $0.075 | $0.3 | 0.07× |
| MiniMax M3 | $0.15 | $0.6 | 0.15× |
| DeepSeek V4.1 Flash | $0.15 | $0.6 | 0.15× |
| DeepSeek V4 Flash | $0.22 | $0.66 | 0.22× |
| DeepSeek R1 | $0.2899 | $1.1596 | 0.29× |
| DeepSeek V4 Pro | $0.66 | $1.98 | 0.66× |
| GLM-5.3 | $0.7 | $2.2 | 0.70× |
| Qwen3.8 Max | $1 | $3 | — |
| Kimi K3.1 Pro | $1 | $5 | 1.00× |
| Kimi K3 | $1.5 | $7.5 | 1.50× |
On input rate alone, stepping up to Kimi K3.1 Pro costs 1.0× the input rate and dropping to GLM-5.3 cuts it by 30%. Both measured at 2026-11-01, the same check as every other rate on this page.
Similarly priced alternatives
| Similarly priced | Vendor | In / out per 1M | vs this |
|---|---|---|---|
| Grok 4.7 | xAI | $1 / $3 | same |
| Claude Haiku 4.5 | Anthropic | $0.5 / $2.5 | −$1.00 |
| o3 | OpenAI | $1 / $4 | +$1.00 |
Blended comparison (input + output per 1M). Price is one axis These are the three closest to Qwen3.8 Max in blended rate, not interchangeable substitutes for it.
Calling Qwen3.8 Max
The identifier you send is qwen3.8-max. Copy it exactly, because a mismatch
returns a model error rather than a connection error, which sends most people to debug the wrong
thing. Everything else is a base URL argument (Qwen3).8 Max's own SDKs work unchanged.
from openai import OpenAI
client = OpenAI(base_url="https://aicomp.ai/v1", api_key="sk-...")
resp = client.chat.completions.create(
model="qwen3.8-max",
messages=[
{"role": "system", "content": "Answer in one short paragraph."},
{"role": "user", "content": "Explain what changed in this release."},
],
max_tokens=300,
)
# prompt_tokens / completion_tokens 是真实账单的唯一依据 —— 记下来,别猜
print(resp.usage.prompt_tokens, resp.usage.completion_tokens)
Log the usage object on every call, not just while you are optimising. On Qwen3.8 Max output costs 3.0× what input costs, so the same monthly token count bills very differently depending on how much of it comes back as output — measure your own split before extrapolating from the headline input rate, because rates move with vendor promotions.
Setting it up
Pointing an existing integration at Qwen3.8 Max is a base URL change, not a rewrite. Pick your tool:
- Claude Code — set the base URL via environment variables
- Cursor — override the API endpoint in settings
- OpenAI / Anthropic SDK — one
base_urlargument - Python, sync, streaming and async examples
- Cutting the bill — eight levers ranked by effect
What different usage shapes cost on Qwen3.8 Max
A monthly token budget does not convert cleanly into a monthly invoice, and Qwen3.8 Max is an ordinary case rather than an extreme one: output is priced at 3.0× input, below the median of 4.0× across the 226 models in our index. Everything follows from that one number At 5:1 it is manageable, at 1:1 the same token count costs half as much. Below are five shapes real Qwen3.8 Max deployments fall into, each costing it out at the split it actually produces.
| Workload | Tokens | Output share | Monthly cost | vs cheapest in index |
|---|---|---|---|---|
| Classification / tagging 100k short jobs, 300 in / 20 out | 32M | 6% | $36.00 | 31.3× |
| Support triage 20k conversations, 1.5k in / 400 out | 38M | 21% | $54.00 | 23.0× |
| RAG question answering 50k questions, 6k in / 500 out | 325M | 8% | $375.00 | 30.0× |
| Agent loop (coding) 8k sessions, 400k in / 6k out | 3248M | 1% | $3344.00 | 37.3× |
| Long-form generation 5k documents, 2k in / 4k out | 30M | 67% | $70.00 | 16.5× |
The cheapest comparison is GPT-5 nano at $0.025 / $0.2 per 1M — 17.8× cheaper than Qwen3.8 Max on a blended rate. Treat it as a rate floor, not a recommendation: it says nothing about whether GPT-5 nano can do the work you need Qwen3.8 Max for.
Read the table as a sanity check rather than a forecast. If your own output share sits anywhere near 3%, everything above is priced almost entirely at Qwen3.8 Max's $1 input rate; at 40% the $3 output rate has taken the larger half. Nobody's split is exactly the one you assumed when you picked the model, which is why the calculator asks for it before quoting anything.
FAQ
How much does Qwen3.8 Max cost per million tokens?
$1 per million input tokens and $3 per million output tokens. No official USD list price is published for this model, so it is billed at platform rate.
Is Qwen3.8 Max cheaper than buying direct?
There is no published official USD price to compare against for this model, it is billed at platform rate, and the reason to route it through a gateway is access and consolidated billing rather than a discount.
What does Qwen3.8 Max cost per month in practice?
At a 5:1 input-to-output ratio it is about $8.00 a month for light use (5M input tokens) and roughly $800.00 for heavy use (500M input). Agent workloads sit at the high end here because every turn resends the context and Qwen3.8 Max bills output at 3.0x input — see what actually drives Claude Code cost.
Which models cost about the same as Qwen3.8 Max?
The comparison table further up this page lists the three closest to Qwen3.8 Max's $4 blended rate. If you are choosing on cost alone, test the top two on your own prompts — $1 per input token is only half the equation, the other half is how many tokens a model needs before it finishes the task.
How do I start using Qwen3.8 Max?
You need an API key, then point your client at the gateway base URL with qwen3.8-max as the model id. On Qwen3.8 Max it is a one-line change in most SDKs — see the SDK setup guide, or the Claude Code and Cursor guides for those tools. The Qwen3.8 Max snippet is in the calling section above.
What is the Qwen3.8 Max API price per 1M tokens?
$1 per 1M input and $3 per 1M output. The two directions are quoted separately because a request is billed twice (once for what you send, once for what comes back) and on Qwen3.8 Max they differ by 3.0x.
How much more does Qwen3.8 Max charge for output than input?
Output tokens cost 3.0x what input tokens do here — $1 per 1M in against $3 per 1M out. The median output-to-input multiple across our full price index is 4.0x, so this model sits below that line. It matters more than it looks: on Qwen3.8 Max a coding agent's output takes 38% of the bill, so the input rate people usually compare is the smaller half. See why output pricing dominates.
How much does Qwen3.8 Max cost for a coding agent?
About $800.00 a month at 500M input and 100M output tokens, the shape a coding assistant really produces, because every turn resends the whole context and the model writes more than it reads. The biggest lever is not the model but how much context you resend each turn At 800 dollars a month on Qwen3.8 Max, halving the resend roughly halves that. See what actually drives agent cost.
Does Qwen3.8 Max have an official list price?
No, Alibaba does not publish a USD list price for this model, so there is nothing to compare against and it bills at platform rate: $1 in / $3 out per 1M. The reason to route it through a gateway is access and one consolidated bill across vendors, not a discount.