DeepSeek V4 Pro vs GLM 5.3
As of October 21, 2026, GLM 5.3 costs 6% more per input token than DeepSeek V4 Pro ($1.40 vs $1.32 per 1M), and both have a 1M-token context window.
DeepSeek V4 Pro vs GLM 5.3 side by side
| DeepSeek V4 Pro | GLM 5.3 | |
|---|---|---|
| Input, per 1M tokens | $1.32 | $1.40 |
| Output, per 1M tokens | $3.96 | $4.40 |
| Cache read, per 1M tokens | $0.044 | $0.26 |
| Cache write, per 1M tokens | $0 | $0 |
| Context window | 1,000,000 tokens | 1,000,000 tokens |
| Max output | 393,216 tokens | 128,000 tokens |
| Image input | No | Yes |
| Tool calling | Yes | Yes |
| Structured output (JSON) | Yes | Yes |
| Prompt caching | Yes | Yes |
| Reasoning | Yes | Yes |
| Providers on LiteLLM | 18 | 17 |
| Price shown is from | DeepSeek | Z.ai |
| Added to LiteLLM | June 2026 | August 27, 2026 |
Cheapest provider for each
- DeepSeek V4 Pro: Sail at $0.92 input and $2.77 output per 1M tokens (
sail/deepseek-ai/DeepSeek-V4-Pro-0813) - GLM 5.3: Sail at $0.98 input and $3.08 output per 1M tokens (
sail/zai-org/GLM-5.3)
Benchmark scores
| Benchmark | DeepSeek V4 Pro | GLM 5.3 |
|---|---|---|
| Coding and agents | ||
| FrontierCode | 17.6% (none) | 40.1% (max) |
| APEX-Agents | 47.3% | 56.6% |
| Reasoning and knowledge | ||
| GPQA Diamond | 90.9% (high) | 90.9% (max) |
| SimpleQA Verified | 47.0% (max) | 41.0% (max) |
| Math | ||
| FrontierMath (tiers 1-3) | 45.3% (max) | 68.8% (max) |
| FrontierMath (tier 4) | 2.4% (max) | 29.3% (max) |
| OTIS Mock AIME 2024-2025 | 96.7% (max) | 91.1% (max) |
When to pick which
Pick DeepSeek V4 Pro for
- Costs 6% less per input token: $1.32 vs $1.40 per 1M.
- Returns up to 393,216 tokens per response, vs 128,000.
Pick GLM 5.3 for
- Supports image input, which DeepSeek V4 Pro doesn't list.
From differences in the data above only; where the data is equal, no reason is given.
Call DeepSeek V4 Pro or GLM 5.3 with LiteLLM
Both use the OpenAI format through LiteLLM, so switching is a model name change. Set each provider's API key in the environment first.
from litellm import completion
messages = [{"role": "user", "content": "Hello!"}]
# DeepSeek V4 Pro
response = completion(model="deepseek-v4-pro", messages=messages)
# GLM 5.3
response = completion(model="zai/glm-5.3", messages=messages)
# DeepSeek V4 Pro, falling back to GLM 5.3 if the call fails
response = completion(model="deepseek-v4-pro", messages=messages, fallbacks=["zai/glm-5.3"])FAQ
Which is cheaper, DeepSeek V4 Pro or GLM 5.3?
DeepSeek V4 Pro is cheaper at 3 input tokens per output token: $1.98 per 1M tokens blended ($1.32 input, $3.96 output), versus $2.15 ($1.40 and $4.40) for GLM 5.3, as of October 21, 2026.
Which has the larger context window, DeepSeek V4 Pro or GLM 5.3?
Both have a 1,000,000-token context window.
Can I switch from DeepSeek V4 Pro to GLM 5.3 without changing my code?
Yes. Through LiteLLM both use the OpenAI format, so switching means changing the model name from "deepseek-v4-pro" to "zai/glm-5.3", or pointing a LiteLLM gateway model alias at the other model. You can also use one as a fallback for the other.
