Requesty
Fireworks AI

glm-5.1

GLM 5.1 is Z.ai's next generation flagship model built for agentic engineering, with stronger coding capabilities and sustained performance over long horizon tasks with hundreds of iteration rounds. It's a 754B parameter MoE model.

Tool callingCaching
Try glm-5.1CompareDocs

Specifications

Context window202K tokens
Max output25K tokens
API typechat
AddedApr 29, 2026
Model IDfireworks/glm-5.1
Data retentionNo
Used for trainingNo
Provider locationπŸ‡ΊπŸ‡Έ US
Privacy policyFireworks Privacy Policy→

Benchmarks

Released 2026-04-07
Coding Indexcoding
43.4%

Artificial Analysis Coding Index β€” a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.

GPQA Diamondreasoning
86.8%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
51.4%

Artificial Analysis Intelligence Index β€” a composite of multiple evaluations measuring overall model capability.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality β€” always test on your own workload.

Pricing

Input / 1M
$1.40
Output / 1M
$4.40
Cache write
β€”
Cache read / 1M
$0.26
Estimated cost
100K input + 10K output$0.18
1M input + 100K output$1.84
10M input + 1M output$18.40

Requesty charges exactly what the upstream provider charges β€” no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to fireworks/glm-5.1.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="fireworks/glm-5.1",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

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deepseek-v4-pro
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Frequently asked questions

How much does glm-5.1 cost?
glm-5.1 is priced at $1.40 per million input tokens and $4.40 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges β€” we don't add markup.
What is the context window of glm-5.1?
glm-5.1 has a context window of 202K tokens, with a maximum output of 25K tokens per response. That's roughly 269 words of input you can fit in a single prompt.
How does glm-5.1 perform on benchmarks?
glm-5.1 scores 97.7% on τ²-Bench, 86.8% on GPQA Diamond, 51.4% on Intelligence Index. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can glm-5.1 do?
glm-5.1 supports tool calling, prompt caching. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use glm-5.1 with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "fireworks/glm-5.1". The Quickstart above shows Python, JavaScript and cURL snippets.

Access glm-5.1 through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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