Alibaba (Qwen) · Fast / Budget · 1M context window

Qwen 3.8 Flash pricing for math reasoning

$0.001635 per call at 1,500 input / 3,000 output tokens.

Per call

$0.001635

10K calls/mo

$16.35

Cache savings

89% off input

Batch savings

50% off all

Calculate your Qwen 3.8 Flash costs

Adjust token counts, volume, and discount toggles to model your math reasoning spend. Prices verified daily against provider pricing pages.

Configure your usage

1,500
100100K
3,000
5050K
10,000
1001M

Estimated cost

Monthly cost
$16
10,000 calls/month
Cost per call$0.001635
Daily cost$0.545
Input rate$0.15/MTok
Output rate$0.47/MTok
Analyze your real spend

Quick start

Call Qwen 3.8 Flash with the OpenAI Python SDK pointed at DashScope:

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
    api_key=os.environ["DASHSCOPE_API_KEY"],
)
response = client.chat.completions.create(
    model="qwen3.8-flash",
    max_tokens=3000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.001635 per call at standard rates
# Input:  $0.15/MTok
# Output: $0.47/MTok

What drives math reasoning cost

Short problems, long solutions. Input is trivial and output is large because the derivation is the answer, so output rate is effectively the only price that matters. Models differ sharply in how much they show their working, which means two models at the same output rate can differ substantially in real cost per problem.

For Qwen 3.8 Flash specifically, that means output tokens cost 3.1x more than input, at $0.47 vs $0.15 per MTok. At this use case’s 1,500/3,000 token split, output accounts for 86% of the $0.001635 per-call cost.

Complete Qwen 3.8 Flash pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$0.151,500
Output$0.473,000

Prompt caching: 89% off input tokens

Caching drops input cost from $0.15 to $0.02/MTok. For repeated system prompts, that saves $0.000201 per call.

Batch API: 50% off all tokens

Submit requests asynchronously and receive 50% off all token costs. This works best for offline pipelines where latency requirements are flexible.

Monthly cost projections

Monthly volumeCost per callStandard monthlyCached monthlyYou save with caching
10,000 calls$0.001635$16.35$14.34$2.01
50,000 calls$0.001635$81.75$71.7$10.05
100,000 calls$0.001635$163.5$143.41$20.09
500,000 calls$0.001635$817.5$717.04$100.46
1,000,000 calls$0.001635$1,635$1,434.08$200.92

Qwen 3.8 Flash quality benchmarks for math reasoning

Benchmark data for math reasoning is pending for Qwen 3.8 Flash. Test against your own evaluation suite before moving to production.

Benchmark data is not yet available for Qwen 3.8 Flash. We recommend testing against your own evaluation criteria.

Alternative models for math reasoning

22 models score 80+ on math reasoning benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (139% more, 86/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs Qwen
GPT 5.6 LunaGPT$0.20$1.2086/100$0.003900139% more
Gemini 3.6 FlashGemini$0.75$3.7585/100$0.0124657% more
Gemini 3.7 FlashGemini$0.75$3.7588/100$0.0124657% more
Gemini 3.8 FlashGemini$0.75$3.7589/100$0.0124657% more
Claude Sonnet 5Claude$2.00$10.0089/100$0.03301918% more
GPT 5.6 TerraGPT$2.00$12.0091/100$0.03902285% more
GPT 6 SolGPT$2.00$10.0089/100$0.03301918% more
Gemini 3.1 ProGemini$2.00$12.0084/100$0.03902285% more
Grok 4.6Grok$2.00$6.0091/100$0.02101184% more
Grok 4.5Grok$2.00$6.0087/100$0.02101184% more
GPT 5.4GPT$2.50$15.0088/100$0.04882882% more
Claude Sonnet 4.6Claude$3.00$15.0085/100$0.04952928% more
Claude Opus 5.5Claude$4.00$20.0092/100$0.06603937% more
GPT 5.6 SolGPT$4.00$20.0092/100$0.06603937% more
Claude Opus 4.8Claude$5.00$25.0089/100$0.08254946% more
Claude Opus 5Claude$5.00$25.0091/100$0.08254946% more
Claude Opus 4.7Claude$5.00$25.0087/100$0.08254946% more
Claude Opus 4.6Claude$5.00$25.0089/100$0.08254946% more
GPT 5.5GPT$5.00$30.0090/100$0.09755863% more
Claude Fable 5.1Claude$10.00$50.0092/100$0.16509992% more
Claude Fable 5Claude$10.00$50.0090/100$0.16509992% more
GPT 6 AstraGPT$10.00$50.0093/100$0.16509992% more

About Qwen 3.8 Flash

Provider

Alibaba (Qwen)

Tier

Fast / Budget

Context

1M tokens

Released

Aug 2026

Prices from help.aliyun.com/en/model-studio (qwen3.8-flash, read 2026-10-11). Cache hit: $0.016/MTok input. Not yet benchmarked, so never recommended.

Other models from Alibaba (Qwen)

ModelTierInput $/MTokOutput $/MTokContext
Qwen 3.8 MaxFlagship$2.00$6.001M

You can compare Qwen 3.8 Flash head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions

How much does Qwen 3.8 Flash cost for math reasoning per API call?

A typical math reasoning call using Qwen 3.8 Flash costs about $0.001635 per call. This estimate uses 1,500 input tokens and 3,000 output tokens at standard rates. Standard rates are $0.15 per million input tokens and $0.47 per million output tokens.

Is Qwen 3.8 Flash the best model for math reasoning?

Our benchmark data does not yet include a math reasoning ranking for Qwen 3.8 Flash. We recommend testing it against your own evaluation criteria before production usage.

What is the cheapest model for math reasoning with good quality?

The most affordable model for math reasoning above 80/100 quality is GPT 5.6 Luna. It comes from GPT at $0.20 per million input tokens. Output costs $1.20 per million tokens with a quality score of 86/100. GPT 5.6 Luna costs more per call than Qwen 3.8 Flash but scores higher on quality benchmarks for this task type.

How can I reduce my Qwen 3.8 Flash costs for math reasoning?

Three strategies lower Qwen 3.8 Flash costs for this task type effectively. Prompt caching gives a 89% discount on input tokens when reusing system prompts. The batch API gives 50% off all tokens for asynchronous processing workloads. Prompt optimization reduces token counts through more concise instructions and context windows. Combining caching with batching brings your cost from $0.001635 to about $0.000087 per call.

How does Qwen 3.8 Flash pricing compare to other Alibaba (Qwen) models?

Alibaba (Qwen) has 1 other models alongside Qwen 3.8 Flash today: Qwen 3.8 Max at $2.00/$6.00 per million tokens (flagship). The right choice depends on whether your math reasoning workload prioritizes quality, cost, or speed.

What context window does Qwen 3.8 Flash support?

Qwen 3.8 Flash supports a context window of 1M tokens per API call. This sets the maximum combined length of your input prompt and generated response. For math reasoning, typical calls use 1,500 input and 3,000 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.

Track what you spend on AI

This calculator estimates costs based on published rates only. Connect your API usage to see where your money goes and which models drive your spend.