GLM-5.2 vs Qwen3-Max
Side-by-side comparison of API pricing, specs, benchmarks, and capabilities
| Specification |
by Z.AI
2 providers:
Together $1.40/$4.40
Z.AI $1.40/$4.40
|
by Alibaba
|
|---|---|---|
| Overview | ||
| Status | Current flagship Open weights | Current flagship |
| Released | Jun 13, 2026 | Jan 1, 2026 |
| Pricing per million tokens | ||
| Input | $1.40/Mtok | $1.20/Mtok |
| Output | $4.40/Mtok | $6.00/Mtok |
| Blended avg | $2.15/Mtok | $2.40/Mtok |
| Cached input | $0.260/Mtok | — |
| Specifications | ||
| Context window | 1M tokens | 262K tokens |
| Parameters | Proprietary | Proprietary |
| Speed (TPS) | — | — |
| Modalities | ||
| Input |
text
|
text
|
| Benchmarks sources: Vellum LLM Leaderboard / Alibaba model card | ||
| GPQA Diamond | 91.2 | 70 vendor |
| SWE-Bench Verified | 45 vendor | 48 vendor |
| Humanity's Last Exam | 54.7 | 25 vendor |
| ARC-AGI 2 | 30 vendor | 28 vendor |
| AIME 2025 | 70 vendor | 72 vendor |
| MMMLU | 80 vendor | 80 vendor |
| BFCL | 70 vendor | 70 vendor |
| HumanEval | 84 vendor | 86 vendor |
| MATH 500 | 76 vendor | 78 vendor |
| Avg benchmark score | 76 | — |
| Perf / dollar | 35.3 | — |
| Terminal-Bench 2.1 | 81 | — |
| MCP Atlas | 77 | — |
| AIME 2026 | 99.2 | — |
| Independent composite scores each on its own scale — not part of the average above | ||
| LMSYS Chatbot Arena | 1469.4 ELO | 1434.6 ELO |
| AA Intelligence Index | 52.6 | — |
| AA Agentic Index | 45.7 | — |
| AA-Omniscience Index (−100–100) | 4.4 | — |
| GDPval-AA v2 | 1508 ELO | — |
| Providers | ||
| Available from |
Together — $1.40/$4.40/Mtok
Z.AI — $1.40/$4.40/Mtok
|
Alibaba — $1.20/$6.00/Mtok
|
Cost at scale
1M tokens · 50/50 input/output| Volume | GLM-5.2 | Qwen3-Max | Savings |
|---|---|---|---|
| 1M tokens | $2.15 | $2.4 | $0.25 (10.4%) |
| 10M tokens | $21.5 | $24 | $2.5 (10.4%) |
| 100M tokens | $215 | $240 | $25 (10.4%) |
| 1000M tokens | $2150 | $2400 | $250 (10.4%) |
When to pick which
distilled from the pricing and spec data above- cost dominates: $2.15/Mtok blended vs $2.40 — 10.4% less on the same 50/50 token mix
- your workload re-reads context (agents, RAG, long chats): cached input costs $0.260/Mtok — 81% off its list input price, a discount Qwen3-Max doesn't offer
- you need the longer context: 1M tokens vs 262K (3.8×)
- you want open weights — self-host it, fine-tune it, or exit the API entirely; Qwen3-Max is closed
- provider flexibility: available from 2 providers, so you can price-shop hosts or fail over
- this pairing gives Qwen3-Max no edge on price, context, cache discount, or measured performance — pick it only for qualitative fit (ecosystem, compliance, model behavior on your prompts)
The cheaper option here — GLM-5.2 costs $2.15/Mtok blended on Z.AI.
Summary
GLM-5.2 by Z.AI costs $1.40/Mtok input and $4.40/Mtok output, with a 1M-token context window. It supports text input and is available from 2 providers.
Qwen3-Max by Alibaba costs $1.20/Mtok input and $6.00/Mtok output, with a 262K-token context window. It supports text input.
On a blended cost basis, GLM-5.2 is 10.4% cheaper than Qwen3-Max.It also has a larger context window.
The two aren't directly comparable on average benchmark score: GLM-5.2 has published per-benchmark results, while Qwen3-Max does not yet — it is measured today on independent composites (see the table above).
Note: Pricing is per million tokens. Actual costs vary with usage patterns, prompt caching, and batch discounts. Always verify against official provider pricing pages.