DeepSeek vs Qwen vs Kimi vs GLM: Which Chinese LLM Should You Use in 2026?

Chinese frontier LLMs are no longer "cheap alternates" to American models. DeepSeek, Alibaba's Qwen, Moonshot's Kimi and Zhipu's GLM now rank among the world's strongest frontier models — and for developers outside China, they are directly usable today. This guide compares the four families on the things that actually matter when you pick a model: real API prices, context windows, and what each family is genuinely best at.

Snapshot: the four families at a glance

All prices above are live NovAI rates (provider list price, zero platform fee) as of September 2026.

DeepSeek V4: the price-performance benchmark

DeepSeek remains the family that reset global expectations on what frontier inference should cost. The V4 generation spans two tiers on NovAI:

• deepseek-v4-pro — $0.57 in / $1.15 out per 1M tokens, 1M context. Roughly a tenth of comparable US flagship pricing.
• deepseek-v4-flash — $0.08 in / $0.17 out, 1M context. One of the cheapest capable LLM endpoints anywhere; a 10M-token batch job costs under a dollar of input.
• deepseek-v4.1-flash — $0.308 / $1.231, 128K context, plus a vision variant at the same rate.

Choose DeepSeek when: you process high volume (classification, extraction, summarization), you need reasoning quality on a budget, or you are routing agentic workloads where token spend compounds fast.

Qwen3.x: the ecosystem play

Alibaba's Qwen is the widest model family in Chinese AI — text, vision, code and open-weight releases that dominate Hugging Face derivative counts. On the API side, NovAI carries:

• qwen3.8-max — $1.84 / $5.52, 256K context (family flagship).
• qwen3.7-max — $1.16 / $3.48.
• qwen3.6-max-preview — $1.03 / $6.16.
• qwen3-max — $0.565 / $2.65.
• qwen-plus — $0.185 / $0.53, the workhorse tier for production chat and RAG.

Choose Qwen when: you want strong multilingual output (its CJK and Southeast-Asian language coverage is a family strength), you plan to move between open-weight self-hosting and API later, or you are building on Alibaba's broader tool ecosystem.

Kimi K-series: long context and coding specialists

Moonshot AI built Kimi's reputation on long documents, and the K-series keeps that identity while adding dedicated coding tiers:

• kimi-k3 — $2.90 / $14.50, 1M context. The family flagship for hard reasoning over very large inputs.
• kimi-k2.8-preview — $0.93 / $3.89, 256K context.
• kimi-k2.7-code — $0.67 / $3.40, with a highspeed tier ($2.073 / $8.61) for latency-sensitive agent loops.
• kimi-k2.6 / k2.5 — $0.95 / $4.00 and $0.60 / $3.00.

Choose Kimi when: your workload is repository-scale code understanding, long contract/document analysis, or you want a purpose-built coding model cheaper than US coding flagships. (See our companion piece on the best Chinese coding models.)

GLM-5.x: the free-tier aggressor

Zhipu AI's GLM family competes on accessibility. It is the only family here with genuinely free, unlimited API tiers:

• glm-5.3 — $1.25 / $4.00, 1M context (flagship).
• glm-5.3-flash — $0.08 / $0.28, 1M context.
• glm-5.2 / 5.1 / 5 — $1.19/$3.74, $1.05/$3.96, $0.60/$1.92.
• glm-5-turbo & glm-5v-turbo (vision) — $1.08 / $3.69.
• Free forever: glm-4.6v-flash (vision), glm-4.7-flash, glm-4.1v-thinking-flash — unlimited at $0 on NovAI.

Choose GLM when: you are prototyping (free tiers mean zero-cost iteration), you need cheap vision-language work, or you want a balanced mid-price flagship with 1M context.

Head-to-head: what does 1B tokens cost?

Blended cost of 1 billion tokens (assume 4:1 input:output), at NovAI list prices:

The spread between the cheapest and most expensive capable endpoint is more than 50x — which is why serious teams route by task instead of picking one model.

Call all four through one OpenAI-compatible API

Every model above is available on NovAI at provider list price with zero platform fee, behind a single OpenAI-compatible base URL. Switching families is a one-line change:

from openai import OpenAI

client = OpenAI(
    api_key="sk-novai-YOUR_KEY",
    base_url="https://aiapi-pro.com/v1"
)

# DeepSeek for bulk extraction...
r1 = client.chat.completions.create(model="deepseek-v4-flash",
    messages=[{"role":"user","content":"Extract entities from: ..."}])

# ...Kimi for repo-scale code questions...
r2 = client.chat.completions.create(model="kimi-k2.7-code",
    messages=[{"role":"user","content":"Review this module: ..."}])

# ...GLM for free prototyping.
r3 = client.chat.completions.create(model="glm-4.7-flash",
    messages=[{"role":"user","content":"Draft a product tagline"}])

Registration takes about 60 seconds, includes $2 free credit (no card required), and accepts USDT (TRC20) or credit card (Visa / Mastercard / UnionPay) for top-up — no Chinese phone number, no VPN, no Alipay.

FAQ

Which Chinese LLM is best for coding in 2026?

Kimi K2.7 Code and DeepSeek V4 Pro are the most common picks; GLM-5.x is competitive at mid price. See the full breakdown in Best Chinese AI Coding Models 2026.

Can I use these models outside China without a Chinese phone number?

Yes. NovAI proxies all four families from Hong Kong infrastructure with USD billing, card and USDT payment. Details in this guide.

Which family is cheapest for high-volume production?

deepseek-v4-flash at $0.08/$0.17 per 1M tokens is the cheapest capable endpoint among the four families; GLM's free flash tiers are cheaper still for workloads that tolerate flash-level quality.

Are these prices marked up?

NovAI charges provider list price with zero platform fee — the token price shown is the token price billed.