GLM 5.3 Flash vs Llama 3.3 70B Instruct

	GLM 5.3 Flash	Llama 3.3 70B Instruct
Provider	Z.ai	Meta
Model id	`zai-org/GLM-5.3-Flash`	`meta-llama/Llama-3.3-70B-Instruct-Turbo`
Input price	$0.20 / 1M tokens	$1.35 / 1M tokens
Output price	$0.66 / 1M tokens	$1.35 / 1M tokens
Context window	1M tokens	131K tokens
Capabilities	Chat, Reasoning, Tool calling, JSON mode, 1M context	Chat, Tool calling, JSON mode, Multilingual
Weights	Open	Open
Availability	Available on Inference APIs	Available on Inference APIs
Rate limits	No daily caps; pay per request	No daily caps; pay per request
Time to first token	0.38 s	1.29 s
Output speed	265.6 tokens / s	67.5 tokens / s

Cost for 1M input + 1M output tokens

GLM 5.3 Flash

$0.86

Llama 3.3 70B Instruct

$2.7

GLM 5.3 Flash is about 68% cheaper for this workload at list price.

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.
Llama 3.3 70B Instruct — Meta's instruction-tuned 70B model. Still served here after its retirement on Groq — the same llama-3.3-70b-versatile id works unchanged.

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.