GLM 5.3 Flash vs GPT-OSS 120B on Groq

	GLM 5.3 Flash	GPT-OSS 120B on Groq
Provider	Z.ai	Groq
Model id	`zai-org/GLM-5.3-Flash`	`openai/gpt-oss-120b`
Input price	$0.20 / 1M tokens	$0.15 / 1M tokens
Output price	$0.66 / 1M tokens	$0.75 / 1M tokens
Context window	1M tokens	131K tokens
Capabilities	Chat, Reasoning, Tool calling, JSON mode, 1M context	Chat, Reasoning, Tool calling, JSON mode
Weights	Open	Open
Availability	Available on Inference APIs	Available
Rate limits	No daily caps; pay per request	Free tier: 30 RPM, 1,000 RPD, 8K TPM, 200K TPD. Developer-tier upgrades paused as of Sep 2026.
Time to first token	0.38 s	not measured
Output speed	265.6 tokens / s	not measured

Cost for 1M input + 1M output tokens

GLM 5.3 Flash

$0.86

GPT-OSS 120B on Groq

$0.9

GLM 5.3 Flash is about 4% cheaper for this workload at list price. Price is only part of it: free tiers and usage tiers cap how much you can send per day, and a retired model is unavailable at any price. The "Rate limits" row above is the practical difference for a production app.

Measured speed

Speed figures for Inference APIs models are medians of three runs from a European client on 2026-09-16, against the public endpoint, using a ~120-word generation prompt (chat), a 300-character paragraph (speech) or a -second clip (transcription). External models are not measured here; treat "not measured" as unknown, not slow.

When to pick which

GLM 5.3 Flash — Z.ai's fast GLM 5.3 model with tool calling, JSON mode and a 1M-token context, at a low per-token price.
GPT-OSS 120B on Groq — Free tier: 30 RPM, 1,000 RPD, 8K TPM, 200K TPD. Developer-tier upgrades paused as of Sep 2026.

Try GLM 5.3 Flash

Same OpenAI request shape; the change is the base URL and key. Full parameters, aliases and pricing on the model page.

curl https://api.inferenceapis.com/v1/chat/completions \
  -H "Authorization: Bearer $INFERENCE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "zai-org/GLM-5.3-Flash",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Hello! What can you do?"}
    ]
  }'

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.inferenceapis.com/v1",
    api_key=os.environ["INFERENCE_API_KEY"],
)
response = client.chat.completions.create(
    model="zai-org/GLM-5.3-Flash",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello! What can you do?"},
    ],
)
print(response.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.inferenceapis.com/v1",
  apiKey: process.env.INFERENCE_API_KEY,
});
const response = await client.chat.completions.create({
  model: "zai-org/GLM-5.3-Flash",
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Hello! What can you do?" },
  ],
});
console.log(response.choices[0].message.content);

External prices and limits come from the linked provider pages and were verified on 2026-09-16. Spotted a change? Tell us.