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GLM-5.2 API pricing

6 providers serve GLM-5.2. GLM-5.2 is an open-weight model (MIT) with 744B total parameters, 40B active per token (mixture-of-experts), up to 1049K context. Prices below are per 1M tokens, cheapest input first (self-hosting math further down).

Refreshed 2026-08-23 · list prices from provider APIs
Input floor $0.610/1M at Scx AI Output floor $1.98/1M at Scx AI Find your workload winner →
Provider Input $/1M Output $/1M Cache read $/1M Context
Scx AI $0.610 $1.98output floor $0.220 1049K
OpenRouter marketplace quote $0.966 $3.04 $0.193 1049K Use
Cloudflare $1.40 $4.40 $0.260 262K Use
Alibaba Model Studio $1.40 $4.40 $0.280 1049K Use
Fireworks AI $1.40 $4.40 $0.140 1049K Use
Mistral AI $1.40 $4.40 $0.140 1049K Use

The cheapest way to run GLM-5.2

On an illustrative 70M-input / 30M-output monthly workload, today's lowest listed cost is roughly $102/month, at Scx AI. Input-heavy, output-heavy and cache-heavy workloads can produce different winners. Use the live mix calculator below rather than combining floors from two different providers. On output-token cost alone, a busy self-hosted deployment can work out cheaper (~$1.65/1M output on 6× MI300X). See the math below. Run your own numbers in the breakeven calculator, or read the breakeven math.

Your actual monthly cost

Uses today's list prices

Cache read uses the listed cache rate where available; otherwise it falls back to normal input price. Batch, write-cache, volume and negotiated discounts are excluded.

Or run it yourself: GLM-5.2 self-hosting economics

GLM-5.2 is open-weight (MIT), so the API price above competes with the GPU-hour market. 744B total parameters (MoE, ~40B active per token) needs roughly 1024 GB VRAM at FP8 or 512 GB at INT4, KV-cache headroom included.

No single GPU fits GLM-5.2 at FP8 (1024 GB needed), so it needs a multi-GPU node. Cheapest tracked option: 6× MI300X (192 GB each) at roughly $3.00/hr total (RunPod). Rent 6× MI300X at RunPod → INT4 quantization drops the requirement to 512 GB. Tune it in the calculator.
Breakeven estimate: a well-batched vLLM deployment on 6× MI300X ($3.00/hr) at ~1013 aggregate tok/s and 50% utilization works out to roughly $1.65 per 1M output tokens, versus $1.98 via the cheapest output-token API (Scx AI). Self-hosting wins on cost if you can keep the GPU busy. Planning estimate: throughput varies with hardware, quantization, batch size and context. Tune it in the calculator.

Related models

ModelCheapest in $/1MCheapest out $/1MProviders
GLM-4.7 $0.400 $1.50 10
GLM-4.6 $0.400 $1.75 8
GLM-4.5 Air $0.125 $0.450 7
GLM-4.5 $0.400 $1.60 6
GLM-5 $0.800 $2.56 5
GLM-5.1 $1.05 $3.50 4

FAQ

What is the cheapest API for GLM-5.2?

As of 2026-08-23, the lowest input price for GLM-5.2 is Scx AI at $0.610 per 1M input tokens. The lowest output price is Scx AI at $1.98 per 1M output tokens. The cheapest provider for a real workload depends on its input/output mix. The next-lowest input price is OpenRouter at $0.966, a 58% difference.

How much VRAM do you need to self-host GLM-5.2?

GLM-5.2 has 744B parameters, so plan for roughly 1024 GB of VRAM at FP8 or 512 GB at INT4/AWQ, KV-cache headroom included. That exceeds a single GPU. A typical node is 6× MI300X.

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