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There is no reliable country-wide winner. A lower-priced API can save money on a specific workload, but the answer depends on its input and output volume, cache use, context length, deployment region, and whether the models meet the same quality bar. The listed prices below were verified on October 7, 2026; check the provider’s current rate card and your account’s regional terms before buying.
What the listed prices show
The clearest comparison is between named APIs, not Chinese and US models as broad categories. The table gives listed prices per 1 million tokens. Chinese-model USD figures below are LLM Abacus conversions of official CNY list prices at ¥6.7119 per US dollar, verified by that comparison page on October 7, 2026. They are not guaranteed checkout rates for your region. OpenAI’s figure is its published standard short-context price.
| Model | Input per 1 million tokens | Output per 1 million tokens | Price basis |
|---|---|---|---|
| DeepSeek V4 Flash | $0.30 | $1.19 | LLM Abacus converted figure |
| DeepSeek V4 Pro | $1.34 | $4.02 | LLM Abacus converted figure |
| Qwen3.5 Flash | $0.030 | $0.30 | LLM Abacus converted figure |
| Qwen3.7 Max | $1.79 | $5.36 | LLM Abacus converted figure |
| Kimi K2.6 | $0.97 | $4.02 | LLM Abacus converted figure |
| GLM-5.1 | $0.89 | $3.58 | LLM Abacus converted figure |
| GPT-6.1 Sol | $1.00 | $5.00 | OpenAI-listed standard short-context price |
Sources: LLM Abacus’s Chinese API price comparison and OpenAI’s API pricing page. OpenAI labels its amounts “Prices per 1M tokens.” Its page also lists a higher long-context tier, so the standard figures are not a blanket rate for every request.
Do these 3 things before closing this tab:
1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteAt face value, Qwen3.5 Flash has the lowest input and output rates in this set. That does not establish it as the cheapest choice for every application: a system that needs more tokens, retries, or a more capable model can erase a lower per-token rate. The available figures also do not establish that any two listed models produce equivalent results.
#1 Best Overall
How to estimate a workload’s token bill
For a simple request with no cached input or other special pricing, estimate input and output separately:
(input tokens ÷ 1,000,000 × input rate) + (output tokens ÷ 1,000,000 × output rate)
For example, suppose a workload uses 1 million input tokens and 200,000 output tokens in the same billing period. Applying the listed rates gives:
- DeepSeek V4 Flash: $0.30 for input + $0.238 for output = $0.538.
- GPT-6.1 Sol: $1.00 for input + $1.00 for output = $2.00.
This is a rate calculation, not a quality or performance comparison. It assumes those token volumes, standard short-context pricing for GPT-6.1 Sol, and no cache discounts, batch rates, tools, taxes, or other charges. If the models do not meet the same task requirements at those volumes, the totals are not an apples-to-apples measure of value.
Check pricing features that can change the result
Cached input
Repeated prompt content may qualify for a different cached-input rate, depending on the provider, model, and request. The comparison page lists cached input at $0.006 per million tokens for DeepSeek V4 Flash, $0.045 for DeepSeek V4 Pro, $0.16 for Kimi K2.6, and $0.19 for GLM-5.1. Treat these as converted secondary figures, and confirm cache eligibility and any cache-write charge on the vendor’s applicable rate card. DeepSeek’s official pricing documentation distinguishes input, cached input, output, and model ID; use the live card for the exact model and rate category.
Batch requests
Alibaba Cloud Model Studio says supported batch calls are charged at 50% of the real-time inference unit price. That rate applies only to eligible batch calls, not automatically to all Qwen usage. Confirm that the model and request qualify on Alibaba Cloud Model Studio’s pricing page.
Long context, region, and endpoint
A long prompt can cross into a higher pricing tier, and the model family’s name alone does not tell you which rate applies. OpenAI’s published pricing page shows a higher long-context tier than its standard short-context rate. Alibaba Cloud’s official Model Studio price list presents CNY rates by model and regional sections; the applicable endpoint and deployment scope matter. Confirm the region, endpoint, currency, context tier, and account eligibility before estimating your bill.
Compare the workload, not just the rate card
A useful cost comparison holds the workload constant: the same input and output token volumes, request pattern, and minimum acceptable result. Then compare these factors:
- Input versus output mix: output rates can be several times higher than input rates, so an output-heavy application may rank models differently from an input-heavy one.
- Cache hit rate: estimate what share of input can actually use cached pricing rather than assuming every prompt qualifies.
- Context requirements: a model’s context limit and any long-context surcharge affect whether it can handle the task economically.
- Batch eligibility: include a batch discount only for calls that meet the provider’s rules and can tolerate the batch workflow.
- Region and billing terms: currency conversion is not the same as an account’s final rate. Payment method, taxes, contractual terms, regional availability, and endpoint pricing can affect the amount charged.
- Task-specific quality: compare the results against your application’s quality bar. A cheaper model that requires longer prompts, extra retries, or human correction may cost more in practice.
No controlled same-task test of quality, latency, reliability, or total cost is established by the prices here. The rate cards answer what providers list for token usage; they do not prove that one model can replace another.
Which API should you choose?
Start with the named models available to your account, then calculate each candidate’s input and output cost using representative token counts. Add any confirmed cache, batch, and long-context pricing, and verify the exact regional endpoint. Finally, test candidates on the same real tasks and exclude any that miss your quality or operational requirements. On listed rates alone, some Chinese APIs are markedly cheaper than GPT-6.1 Sol for the token volumes in the example; that is a model-and-workload comparison, not evidence that Chinese APIs always save money.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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