DeepSeek vs Qwen vs Kimi vs GLM — Chinese AI Models 2026 Complete Comparison

2026-05-20 — by Global API Team

deepseek-vs-qwen kimi-vs-glm chinese-ai-models llm-comparison-2026 deepseek-v4-flash qwen3 kimi-k2 glm-5 api-comparison comparison

China's AI ecosystem has produced four powerhouse model families: DeepSeek, Qwen, Kimi, and GLM. Each has distinct strengths — but choosing between them without testing is difficult.

We've tested all four via Global API's unified endpoint. This comparison covers pricing, quality, speed, and best use cases with real data.

TL;DR: DeepSeek V4 Flash wins on price-to-performance. Qwen has the widest model range. Kimi leads on reasoning benchmarks. GLM excels at Chinese-language tasks.

Quick Comparison Table

| Feature | DeepSeek | Qwen | Kimi | GLM | |---------|----------|------|------|-----| | Developer | DeepSeek (幻方) | Alibaba (阿里) | Moonshot AI (月之暗面) | Zhipu AI (智谱) | | Price Range | $0.25-$2.50/M | $0.01-$3.20/M | $3.00-$3.50/M | $0.01-$1.92/M | | Best Budget Model | V4 Flash @ $0.25/M | Qwen3-8B @ $0.01/M | N/A (all premium) | GLM-4-9B @ $0.01/M | | Best Overall | V4 Flash @ $0.25/M | Qwen3-32B @ $0.28/M | K2.5 @ $3.00/M | GLM-5 @ $1.92/M | | Code Generation | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | | Chinese Language | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | | English Language | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | | Reasoning | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | | Speed | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐ | | Vision/Multimodal | Limited | ✅ (VL, Omni) | ❌ | ✅ (GLM-4.6V) | | Context Window | Up to 128K | Up to 128K | Up to 128K | Up to 128K | | API Compatibility | OpenAI ✅ | OpenAI ✅ | OpenAI ✅ | OpenAI ✅ |

DeepSeek: The Value King

Key Models

| Model | Output $/M | Best For | |-------|-----------|----------| | V4 Flash | $0.25 | Daily use, coding, content | | V3.2 | $0.38 | Latest architecture | | V4 Pro | $0.78 | Production quality | | R1 (Reasoner) | $2.50 | Complex math, logic | | Coder | $0.25 | Code-specific tasks |

Strengths

Best price-to-performance ratio — V4 Flash at $0.25/M rivals GPT-4o quality
Excellent code generation — Consistently top-tier on HumanEval and MBPP
Fast — V4 Flash achieves ~60 tokens/sec, among the fastest
Strong English — Performance on par with Western models
Open-weight heritage — Built on transparent research

Weaknesses

Limited vision capabilities — No native image understanding
Chinese can be slightly weaker — GLM and Kimi edge it out on Chinese benchmarks
Less model variety — Fewer size options compared to Qwen

Example: Switch to DeepSeek V4 Flash

from openai import OpenAI

client = OpenAI(
    api_key="ga_xxxxxxxxxxxx",
    base_url="https://global-apis.com/v1"
)

response = client.chat.completions.create(
    model="deepseek-v4-flash",  # V4 Flash
    messages=[{"role": "user", "content": "Explain quantum computing in 100 words"}]
)
print(response.choices[0].message.content)

Qwen: The Swiss Army Knife

Key Models

| Model | Output $/M | Best For | |-------|-----------|----------| | Qwen3-8B | $0.01 | Ultra-light tasks | | Qwen3-32B | $0.28 | General purpose | | Qwen3-Coder-30B | $0.35 | Code generation | | Qwen3-VL-32B | $0.52 | Image understanding | | Qwen3-Omni-30B | $0.52 | Multimodal | | Qwen3.5-397B | $2.34 | Enterprise reasoning |

Strengths

Widest model range — From $0.01/M to $3.20/M, covers every budget
Strong vision models — Qwen3-VL series for image tasks
Omni-modal — Audio, video, image all in one model
Alibaba backing — Enterprise-grade infrastructure
Active development — Frequent new releases (Qwen3.5, Qwen3.6)

Weaknesses

Inconsistent naming — Model versions can be confusing
Mid-range English — Good but not DeepSeek-level
Some models overpriced — Qwen3.6-35B at $1/M is steep

Example: Qwen3-32B for General Tasks

response = client.chat.completions.create(
    model="Qwen/Qwen3-32B",
    messages=[{"role": "user", "content": "Write a Python function to merge two sorted lists"}]
)

Kimi: The Reasoning Specialist

Key Models

| Model | Output $/M | Best For | |-------|-----------|----------| | K2.5 | $3.00 | Top-tier general purpose | | K2.6 | $3.50 | Latest architecture | | K2-Thinking | $3.00 | Complex reasoning | | K2-Instruct | $3.00 | Instruction following |

Strengths

Best reasoning capability — Consistently tops Chinese AI benchmarks
Excellent Chinese — Native Chinese understanding and generation
Strong instruction following — K2-Instruct excels at complex prompts
Moonshot's focus — Dedicated team, rapid iteration

Weaknesses

Most expensive — $3.00-$3.50/M, no budget option
No vision — Text-only
Slower — Thinking models have longer latency
Limited model sizes — No small/cheap variants

Example: Kimi K2.5 for Complex Analysis

response = client.chat.completions.create(
    model="kimi-k2.5",
    messages=[{"role": "user", "content": "Analyze the following financial report and identify key risks..."}]
)

GLM: The Chinese Language Expert

Key Models

| Model | Output $/M | Best For | |-------|-----------|----------| | GLM-4-9B | $0.01 | Lightweight tasks | | GLM-4-32B | $0.56 | Strong mid-range | | zai-org/GLM-4.6 | $1.50 | Latest architecture | | GLM-4.6V | $0.80 | Vision tasks | | GLM-5 | $1.92 | Top-tier Chinese |

Strengths

Best Chinese-language quality — Native Chinese understanding unmatched
Good vision models — GLM-4.6V at $0.80/M is affordable
Budget options — GLM-4-9B at $0.01/M with decent quality
Zhipu's expertise — Longest-running Chinese LLM team
Active research — GLM-5 with competitive benchmarks

Weaknesses

Weaker English — English tasks lag behind DeepSeek
Smaller community — Fewer third-party tools and tutorials
Code generation average — Not as strong as DeepSeek/Qwen for coding

Example: GLM-5 for Chinese Content

response = client.chat.completions.create(
    model="glm-5",
    messages=[{"role": "user", "content": "写一篇关于人工智能发展趋势的短文"}]
)

Head-to-Head: Which Model for Which Task?

| Task | Winner | Runner-up | Why | |------|--------|-----------|-----| | General Chat (English) | DeepSeek V4 Flash | Qwen3-32B | Best quality at lowest price | | General Chat (Chinese) | GLM-5 | Kimi K2.5 | Native Chinese excellence | | Code Generation | DeepSeek V4 Flash | Qwen3-Coder-30B | Consistently top benchmarks | | Complex Reasoning | Kimi K2.5 | DeepSeek-R1 | Top reasoning scores | | Image Understanding | Qwen3-VL-32B | GLM-4.6V | Qwen VL leads on benchmarks | | Budget/MVP Testing | Qwen3-8B | GLM-4-9B | Both at $0.01/M | | Production SaaS | DeepSeek V4 Flash | Qwen3-32B | Reliability + cost | | Academic Research | Kimi K2.5 | DeepSeek-R1 | Best reasoning | | Multilingual | DeepSeek V4 Flash | Qwen3-32B | Strongest English+Chinese | | Long Documents | Qwen3.5-27B | DeepSeek V3.2 | 128K context at good price |

Migration: Switching Between Models

All four model families share OpenAI-compatible API. Switching is a one-line change:

# From DeepSeek to Qwen
response = client.chat.completions.create(
    model="Qwen/Qwen3-32B",     # ← Just change this
    messages=[...]
)

# From Qwen to Kimi
response = client.chat.completions.create(
    model="kimi-k2.5",           # ← One line
    messages=[...]
)

# From Kimi to GLM
response = client.chat.completions.create(
    model="glm-5",               # ← One line
    messages=[...]
)

All via the same base_url="https://global-apis.com/v1" and same API key.

Price-Performance Matrix

Combined score (1-10) factoring quality, speed, and price:

| Model | Quality | Speed | Price | Overall Value | |-------|---------|-------|-------|-------------------| | DeepSeek V4 Flash | 8.5 | 9 | $0.25 | 9.2/10 🥇 | | Qwen3-32B | 8.0 | 8 | $0.28 | 8.8/10 🥈 | | DeepSeek V4 Pro | 9.0 | 7 | $0.78 | 7.5/10 | | GLM-5 | 8.8 | 7 | $1.92 | 6.8/10 | | Kimi K2.5 | 9.2 | 6 | $3.00 | 6.5/10 | | Qwen3.5-397B | 9.0 | 5 | $2.34 | 6.2/10 |

Recommendation Flowchart

What's your primary need?

├─ "Cheapest possible" → Qwen3-8B ($0.01/M) or GLM-4-9B ($0.01/M)
│
├─ "Best overall value" → DeepSeek V4 Flash ($0.25/M) 🏆
│
├─ "Strongest Chinese" → GLM-5 ($1.92/M) or Kimi K2.5 ($3.00/M)
│
├─ "Complex reasoning" → Kimi K2.5 ($3.00/M) or DeepSeek-R1 ($2.50/M)
│
├─ "Image/video tasks" → Qwen3-VL-32B ($0.52/M)
│
├─ "Code assistant" → DeepSeek V4 Flash ($0.25/M) or Qwen3-Coder ($0.35/M)
│
└─ "Not sure, try everything" → Start with 100 free credits on Global API

All models tested via Global API — one API key, one endpoint, 184 models. Prices verified May 20, 2026.

DeepSeek vs Qwen vs Kimi vs GLM — Chinese AI Models 2026 Complete Comparison

Quick Comparison Table

DeepSeek: The Value King

Key Models

Strengths

Weaknesses

Example: Switch to DeepSeek V4 Flash

Qwen: The Swiss Army Knife

Key Models

Strengths

Weaknesses

Example: Qwen3-32B for General Tasks

Kimi: The Reasoning Specialist

Key Models

Strengths

Weaknesses

Example: Kimi K2.5 for Complex Analysis

GLM: The Chinese Language Expert

Key Models

Strengths

Weaknesses

Example: GLM-5 for Chinese Content

Head-to-Head: Which Model for Which Task?

Migration: Switching Between Models

Price-Performance Matrix

Recommendation Flowchart

Part of DeepSeek API Complete Guide

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