DataLLM LabGLM-5 vs DeepSeek in 2026: The Open-Weights Showdown
GLM-5.2 (Zhipu/Z.ai) and DeepSeek are the two heavyweights of the open-weights frontier — both MIT-licensed, both self-hostable, both a fraction of the Western frontier's price. The split: GLM-5.2 is the #1 open-weights model on the independent Artificial Analysis Index with a 1M context, while DeepSeek is cheaper per token and the cheapest capable baseline. This guide compares them on benchmark, license, cost, and where each wins.
The short answer
GLM-5.2 for top open-weights quality; DeepSeek for the lowest cost. Both are MIT-licensed and self-hostable. GLM-5.2 is the #1 open-weights model on the independent Artificial Analysis Index with a 1M context; DeepSeek is 6-13x cheaper per token and the cheapest capable baseline. The gap is small enough that routing both is the smart move.
Side by side
| GLM-5.2 (Z.ai) | DeepSeek | |
|---|---|---|
| Flagship | GLM-5.2 | V4-Pro / V3.2 |
| AA Intelligence Index | #1 open-weights (51) | Strong, below GLM-5.2 |
| Cheapest tier (in/out) | GLM-5 $1.00 / $3.20 | V3.2 $0.23 / $0.34 |
| License | MIT | MIT |
| Context window | 1M | Capable |
| Best at | Top open quality, agentic, 1M context | Cheapest baseline, reasoning |
What they cost to run
DeepSeek wins every row on price; GLM-5.2 charges more for its Index lead:
| Monthly workload | DeepSeek V3.2 | DeepSeek V4-Pro | GLM-5.2 | GLM-5 |
|---|---|---|---|---|
| Support chatbot | $13.3 | $27.8 | $109 | $78.4 |
| RAG / knowledge base | $52.8 | $104 | $368 | $264 |
| Coding agent | $26.9 | $56.5 | $222 | $160 |
| Batch extraction | $37.2 | $72.2 | $245 | $176 |
| Content generation | $18.2 | $43.5 | $204 | $148 |
How they did in our test
We ran both through our executed-code coding benchmark — nine tasks graded by running the code against hidden tests (see our methodology). GLM-5.2 scored 9/9, though as a moderate reasoner (~560 reasoning tokens per task) it cost about $1.99 per 1,000 tasks. DeepSeek's current line is now V4 (V4-Flash and V4-Pro; the V3.2 in the table above is the prior budget tier), and its efficiency model V4-Flash scored 9/9 at about $0.13 per 1,000 tasks — the best cost-per-correct-answer we measured. That's the whole comparison in miniature: DeepSeek wins on cost-efficiency, GLM-5.2 leads the open-weights intelligence Index. Note both current flagships also offer a 1M-token context, so on context length it's effectively a tie.
Where GLM-5.2 wins
- Top open-weights Index — #1 open model on the independent Artificial Analysis Index.
- 1M context — larger than DeepSeek for big documents/codebases.
- Agentic engineering — tuned for long-horizon coding/agent work.
Where DeepSeek wins
- Price — 6-13x cheaper per token; the cheapest capable baseline.
- Reasoning reputation — strong chain-of-thought at a tiny price.
- Value at volume — the lowest bill for high-volume workloads.
Which to pick
Top open quality GLM-5.2
- When you want the best open-weights model and the 1M context.
Cheapest DeepSeek V3.2
- The lowest-cost capable baseline for high volume.
Both self-host Either
- MIT weights — pick by GPU fit and capability need.
Best move Route both
- DeepSeek default, escalate to GLM-5.2 for harder/longer-context work.
Route GLM-5.2 and DeepSeek from one key
GLM-5.2, DeepSeek V3.2, and 300+ more — one OpenAI-compatible endpoint, cheapest-first routing with failover.
FAQ
Is GLM-5.2 better than DeepSeek?
On the independent Index, GLM-5.2 ranks #1 open-weights, ahead of DeepSeek. DeepSeek counters with lower price and strong reasoning. GLM-5.2 for top open quality; DeepSeek for cheapest.
Is GLM-5 or DeepSeek cheaper?
DeepSeek — V3.2 $0.23/$0.34 vs GLM-5.2 $1.40/$4.40 (~6-13x). On a coding agent, ~$27/mo vs $222.
Are both open source?
Yes — both MIT-licensed open-weights on Hugging Face, self-hostable, and OpenAI-SDK-compatible via their APIs.
Which has the bigger context window?
GLM-5.2 (1M tokens). DeepSeek's context is capable but smaller. GLM-5.2 for very large single-pass inputs.
GLM-5 or DeepSeek for coding?
Both strong, cheap coders — GLM-5.2 (agentic, top open Index, vendor SWE-bench Pro 62.1) vs DeepSeek V4 (all-round, reasoning, cheaper). Test both.
Should I use GLM-5 or DeepSeek?
Route both — DeepSeek as cheapest default, GLM-5.2 for top quality or 1M context, with failover. One key via DataLLM Lab.
Which is the best open-weights model in 2026?
By the independent Index, GLM-5.2 at release. DeepSeek is the value leader and close behind. Best depends on capability (GLM-5.2) vs cost (DeepSeek).
Can I self-host both?
Yes — both ship MIT weights on Hugging Face. GLM-5.2 is ~744-753B/40B; pick by your GPU budget and capability need.