glm-5.1 API — compare providers

The same model (glm-5.1) is served by 15 providers; Baidu is the cheapest at $3.764/1M blended — the priciest (Venice) costs 70% more. On quality, glm-5.1 scores 1466 on the LMArena (Chatbot Arena) — so the cheapest endpoint is also the best value per dollar here.

LicenseMITopen weights · permissive · terms
Knowledge cutoffJanuary 2026source · ranked
Quality (Elo)1466LMArena (Chatbot Arena) · source
Intelligence41Artificial Analysis Intelligence Index · source · ranked

Quality and intelligence scores are attached to the model itself — identical whichever provider serves it. Verified 2026-09-04.

RankProviderInput /1MOutput /1MBlended /1MValue (Elo/$)
1Baidu$0.9086$2.8556$3.764 ← cheapest389 ← best value
2GMICloud$0.91$2.86$3.77389
3Chutes$0.98$3.08$4.06361
4DeepInfra$1.05$3.5$4.55322
5SiliconFlow$1.19$3.74$4.93297
6AtlasCloud$1.26$3.96$5.22281
7Phala$1.21$4.2$5.41271
8Alibaba$1.33$4.18$5.51266
9DigitalOcean$1.3$4.3$5.6262
10Crusoe$1.2$4.4$5.6262
11Novita AI$1.38$4.4$5.78254
12Nebius$1.4$4.4$5.8253
13Friendli$1.4$4.4$5.8253
14Z.AI$1.4$4.4$5.8253
15Venice$1.54$4.84$6.38230

Value = model Elo ÷ blended price per 1M tokens. Since the model's quality is identical across providers, the cheapest endpoint is also the best value per dollar.

Prices are per 1M tokens (USD). "Blended" = input + output, for coarse ranking. Same underlying model, 15 serving providers, 70% spread top to bottom. Context window: 204,800 tokens (131,072 max output) — see how it ranks in biggest context windows. See how this compares across the catalogue in same model, different price, or find the best quality per dollar in the value ranking.

Cost per 1,000 requests by workload

What each provider actually bills for a representative job, not just the sticker price.

ProviderChatbot
1000 in / 500 out
RAG / long context
8000 in / 500 out
Batch summarize
4000 in / 1000 out
Baidu$2.34$8.70$6.49
GMICloud$2.34$8.71$6.50
Chutes$2.52$9.38$7.00
DeepInfra$2.80$10.15$7.70
SiliconFlow$3.06$11.39$8.50
AtlasCloud$3.24$12.06$9.00
Phala$3.31$11.78$9.04
Alibaba$3.42$12.73$9.50
DigitalOcean$3.45$12.55$9.50
Crusoe$3.40$11.80$9.20
Novita AI$3.58$13.24$9.92
Nebius$3.60$13.40$10.00
Friendli$3.60$13.40$10.00
Z.AI$3.60$13.40$10.00
Venice$3.96$14.74$11.00

Estimate your own workload

Input tokens/request:   Output tokens/request:   Requests:

ProviderEstimated cost (USD)

Self-host / quantized builds

Open weights under MIT — you can run glm-5.1 on your own hardware instead of paying per token. Quantized builds lower the memory footprint; whether it fits your GPU or Mac depends on the model's size. Formats: GGUF for llama.cpp / Ollama / LM Studio, AWQ and GPTQ for GPU serving, MLX for Apple silicon.

Links search the live model hubs (Hugging Face, Ollama) so they track new builds as they appear — we don't host weights. Which formats exist depends on what the model owner and community have published.