compare/Glm-5.3vsGemini 3.7 Flash

Glm-5.3 vs Gemini 3.7 Flash

Pricing, context window, capabilities, and release date — pulled from each provider's public docs. Both are available via the same AIgateway OpenAI-compatible endpoint; flip the model string to switch.

RUN BOTH LIVE

Paste a prompt. Watch them race.

Both models stream in parallel through your own AIgateway key. Tokens, latency, and cost update as they arrive.

Sign in to runLive streaming uses your own key. It's free to sign up.
 Glm-5.3
zai-org/glm-5.3
Gemini 3.7 Flash
google/gemini-3.7-flash
ProviderZai-orgGoogle
FamilyGemini 3
Modalitytexttext
Context window1,310,720 tok1,048,576 tok
Max output131,072 tok65,536 tok
Released2026-08-142026-08-14
Input price$1.40 /1M$0.750 /1M
Output price$4.40 /1M$3.75 /1M
Cache read
Toolsyesyes
Streamingyesyes
Visionyes
JSON modeyesyes
Reasoningyes
Prompt caching
Glm-5.3
zai-org/glm-5.3
Full spec →

GLM-5.3 is Z.ai's flagship agentic coding model, pairing a 1M-token context window with reasoning, function calling, and structured outputs to power multi-step, tool-driven development workflows.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
Gemini 3.7 Flash
google/gemini-3.7-flash
Full spec →

Gemini 3.7 Flash is a highly capable, natively multimodal reasoning model optimized for agentic workflows and real-world tasks.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
SWITCH BETWEEN THEM

One key, both models, one line different.

# pip install aigateway-py openai
# aigateway-py: sub-accounts, evals, replays, jobs, webhook verify.
# openai SDK: chat/embeddings/images/audio — drop-in compat per our SDK's own guidance.
from openai import OpenAI

client = OpenAI(
    base_url="https://api.aigateway.sh/v1",
    api_key="sk-aig-...",
)

# Try Glm-5.3
client.chat.completions.create(
    model="zai-org/glm-5.3",
    messages=[{"role":"user","content":"hello"}],
)

# Try Gemini 3.7 Flash — same client, same key
client.chat.completions.create(
    model="google/gemini-3.7-flash",
    messages=[{"role":"user","content":"hello"}],
)
Get an AIgateway keyAdd a third model

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