Chinese LLM vs Claude: API Cost Compared (2026)

Chinese LLM APIs cost a fraction of Claude Sonnet 4.6's $3/$15 per million tokens: DeepSeek V4-Flash bills $0.14/$0.28, GLM-4.6 routes at $0.43/$1.74, and Qwen3-Max at $0.78/$3.90, so the real question is whether your task needs Claude-grade reasoning. The price gap runs from roughly 4x to 21x on input, and it is verified, but it is not a free upgrade. What you trade away is the part that never shows up on the invoice: the consistency you lean on when one wrong answer is expensive.

Chinese LLM vs Claude API cost (verified 2026-06)

Start with the rate card the whole comparison rests on, all per 1,000,000 tokens in USD. Claude Sonnet 4.6 is the anchor at $3.00 input and $15.00 output, captured from a multi-source check against Anthropic's published pricing on 2026-06-26. The Chinese rows below are the cheapest credible general tier from three different families, so this clears the multi-vendor bar by design rather than pushing a single name.

The output column is where the gap really opens. Sonnet's $15.00 against V4-Flash's $0.28 is roughly 54x, against GLM-4.6's $1.74 about 9x, and against Qwen3-Max's $3.90 just under 4x. Output matters more than input for most generative work because models emit far more tokens than they read, so that column is where your bill actually diverges. The practical upshot: the cheaper the model, the more the savings concentrate on the side you spend the most on.

One disclosure that decides how you read this table. DeepSeek V4-Flash was measured on its official api.deepseek.com endpoint, but the GLM, Qwen, Kimi, and MiniMax rows were measured via OpenRouter, a third-party router, not on each vendor's own key. According to DeepSeek API Docs, V4-Flash inputs cost $0.14 and outputs $0.28, which we can quote natively; the OpenRouter-routed prices carry a needs_native_reverify flag because official vendor list prices can differ. Qwen3-Max, for instance, lists around $2.40/$12.00 on Alibaba's international endpoint, well above the $0.78/$3.90 we saw through OpenRouter.

We ran the same call on four families plus Claude (first-hand evidence)

Documentation gives you a rate card. It does not tell you what one real request costs, so we called several models with short general and coding prompts and recorded the raw usage object for each. DeepSeek answered on its official endpoint; the Chinese rivals below answered through OpenRouter, which is how we captured their billed cost directly. The full run lives in our evidence pack.

Two things stood out when we re-read the usage objects. First, every one of these answers landed for a fraction of a US cent, while the same trivial prompt on Claude Sonnet 4.6 (also via OpenRouter, in a sibling test) billed $0.001344, several times more than the priciest Chinese call here. Second, the cheapest was not the slowest. DeepSeek V4-Flash returned in under two seconds on its official endpoint, faster than GLM-4.6's 8.58s or Kimi K2's 7.03s through OpenRouter, which cuts against the "cheap but sluggish" assumption. We re-ran the DeepSeek call to be sure the sub-two-second figure held, and it did.

The DeepSeek cost is not pre-billed in the artifact, so we computed it from the verified official rates: 27 input tokens at $0.14/M is $0.00000378, and 120 output tokens at $0.28/M is $0.0000336, for about $0.0000374 total.

Where the price gap is real and where it is a trap

The honest framing is a tradeoff, not a clean win. On high-volume, well-specified work (classification, extraction, bulk summarization, code scaffolding) a 4x to 21x per-token saving converts almost directly into a smaller invoice with little quality cost, and for those workloads the verdict is easy. Send the bulk to a Chinese model.

The trap is assuming that ratio holds on the work that earns its keep through quality. Claude Sonnet 4.6 sits at $3.00/$15.00 per million tokens, between 4x and 21x above the cheapest Chinese general tiers on input, but its premium buys reasoning consistency that a single failed round-trip can otherwise erase. On a hard architecture decision or a subtle refactor, one extra retry because the cheaper model missed the point can wipe out a 20x token saving. The number to optimize is cost per accepted answer, not cost per token, and that number depends on your task, not on the rate card.

According to DeepSeek API Docs, DeepSeek's only callable models are deepseek-v4-flash and deepseek-v4-pro; the familiar deepseek-chat alias resolves to V4-Flash, so the $0.14/$0.28 row is the rate you actually pay, not a discontinued tier. That matters because stale legacy prices float around the web and would skew any Claude comparison built on them.

Routing is the other variable most buyers miss. According to Z.ai, GLM's official endpoint lists GLM-4.6 around $0.60/$2.20, above the $0.43/$1.74 we measured through OpenRouter, so a vendor-native key is not automatically the cheapest path, and a US-routed reseller price can run higher still. If your reason for choosing a Chinese model is purely cost, the endpoint you actually call is the comparison that matters, not the headline list price.

Verdict: cost vs reasoning, decided by the task

DeepSeek V4-Flash, GLM-4.6, and Qwen3-Max are the right default when volume is high and each individual answer is low-stakes, because a 4x to 54x advantage over Sonnet compounds across millions of calls. Reach for Claude when a single wrong answer is expensive: nuanced reasoning, long-horizon agentic chains, or output a human will not re-check. The common middle path is to route the bulk of traffic to a Chinese model and escalate only the hard cases to Claude, which captures most of the savings without betting your worst-case quality on the cheapest option. For a full ranked breakdown across families, see the hub below.

FAQ

How much cheaper are Chinese LLM APIs than Claude per token? Claude Sonnet 4.6 bills $3.00 input and $15.00 output per million tokens. DeepSeek V4-Flash ($0.14/$0.28) is about 21x cheaper input and 54x cheaper output; GLM-4.6 ($0.43/$1.74, measured via OpenRouter) is roughly 7x and 9x cheaper; Qwen3-Max ($0.78/$3.90, via OpenRouter) is about 4x cheaper on both axes.

What did the same prompt actually cost on each Chinese model? On our live calls via OpenRouter, GLM-4.6 billed $0.00036376 for 32 input and 200 output tokens, Qwen3-Max $0.00027534, Kimi K2 $0.00015852, and MiniMax-M2 $0.000209945. DeepSeek V4-Flash on its official endpoint computed to about $0.0000374 for 27 input and 120 output tokens. Each is a fraction of a US cent.

Are these Chinese prices measured on the vendors' own endpoints? Only DeepSeek. Its $0.14/$0.28 came from the official api.deepseek.com endpoint. GLM, Qwen, Kimi, and MiniMax figures were measured via OpenRouter and carry a needs_native_reverify flag, because official list prices can be higher (Qwen3-Max lists near $2.40/$12.00 on Alibaba International).

Is a cheaper Chinese model always slower than Claude? Not in our test. DeepSeek V4-Flash returned in under two seconds on its official endpoint, faster than GLM-4.6 (8.58s) and Kimi K2 (7.03s) measured through OpenRouter. Latency tracks the model, the routing path, and output length more than the headline price.

When should I still pay for Claude? Pay for Claude when one wrong answer is costly: hard reasoning, long agentic chains, or output nobody re-checks. There its higher per-token price can be cheaper per accepted answer, since a single failed round-trip on a cheaper model can erase a 20x token saving.

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This is part of the best Chinese LLM API hub. For the family-level rate card, see the DeepSeek API pricing hub.

Author: Kevin Fan, Customer Success Manager at China LLM Directory, specializing in Chinese LLM ecosystem pricing. Last verified: 2026-06-26.

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