Claude Opus 4.7 vs GLM-4.5-Air
A side-by-side look at Anthropic's Claude Opus 4.7 and Zhipu AI's GLM-4.5-Air — covering API pricing, context window, latency, coding ability, and real-world fit, so you can pick the right model for what you're building.
Quick Verdict
Cost optimization across both models
Access either model through one API key. Pay only for what you use — save up to 70% vs official pricing.
Overview
Claude Opus 4.7 and GLM-4.5-Air come from different camps — Anthropic versus Zhipu AI — and they split most sharply on price and context. Claude Opus 4.7 runs at $5.00/$25.00 per 1M tokens with a 1M window; GLM-4.5-Air sits at $0.11/$0.28 with 128K of context. Neither is objectively "better" — the right pick depends on what you're shipping.
In practice: Previous Opus generation. Still available; Opus 4.8 is recommended for new projects. Budget-friendly GLM model. Excellent value for bilingual Chinese-English tasks. Both ship through AI API Hub on an OpenAI-compatible endpoint, so you can move between them by changing a single model name — and settle the bill with USDT or USDC, no credit card required.
On cost alone, GLM-4.5-Air is the cheaper of the two (Save $4.89 per 1M input), which adds up fast once real traffic hits. Use the calculator below to model your own volume.
Interactive Cost Calculator
Deep Specs Matchup
| Specification | Claude Opus 4.7 | GLM-4.5-Air |
|---|---|---|
| Provider | Anthropic | Zhipu AI |
| Release Date | 2026-01 | 2026-01 |
| Context Window | 1M | 128K |
| Max Output Tokens | 32,768 | 4,096 |
| Input Price | $5.00/1M | $0.11/1M |
| Output Price | $25.00/1M | $0.28/1M |
| Vision Support | Yes ✓ — image input | No |
| Audio Support | No | No |
| Function Calling / Tool Use | Yes ✓ | Yes ✓ |
| JSON Mode Support | No | No |
| Streaming | No | No |
| Fine Tuning | No | No |
| Rate Limits (RPM/TPM) | 2K RPM | 10K RPM |
| Latency P95 | N/A | N/A |
| Latency P99 | N/A | N/A |
| Status | active | active |
Latency P95/P99: Not publicly disclosed by provider — marked N/A to avoid fabrication. Rate limits shown as published by the provider; plan-dependent where N/A. All data sourced from model-variants.ts.
Pros & Cons Analysis
Claude Opus 4.7
- ✓Long-context reasoning — 1M window handles large documents
- ✓Tool use — function calling for AI agents
- ✓Multimodal — vision/image input supported
- ✗Premium pricing — $5.00/1M input
- ✗Previous version
GLM-4.5-Air
- ✓Cost efficiency — $0.11/1M input, ultra-low token cost
- ✓Tool use — function calling for AI agents
- ✓Most affordable GLM
- ✗No vision support — text-only input
- ✗Previous GLM generation
Benchmark Scores
| Benchmark | Claude Opus 4.7 | GLM-4.5-Air |
|---|---|---|
| MMLU | N/A | N/A |
| HumanEval | N/A | N/A |
| SWE-bench | N/A | N/A |
| GSM8K | N/A | N/A |
| Arena Score | N/A | N/A |
E-E-A-T note: Benchmark data is sourced exclusively from official provider releases stored in our model registry. No estimated or inferred scores are shown.
🧠 Human Decision Summary
→If your workload involves long document reasoning or multi-step instruction following → Claude Opus 4.7 performs better with its 1M context.
→If cost is your primary constraint → GLM-4.5-Air provides ~98% lower cost per 1M tokens.
→If you need function-calling AI agents → both support tool use; choose GLM-4.5-Air for higher-volume cost efficiency.
These recommendations are derived from each model's capabilities and pricing in our registry — not hand-written per page.
🏆 Winner per Dimension
| Category | Winner | Reason |
|---|---|---|
| Coding | Tie | Native code generation + better price-performance |
| Long context | Claude Opus 4.7 | Larger context window (1M) |
| Cost efficiency | GLM-4.5-Air | Lower input price — $0.11/1M vs $5.00/1M |
| Reasoning | Tie | Chain-of-thought / math specialization |
| Multimodal | Claude Opus 4.7 | Vision / image input support |
Real-world Use Cases
Claude Opus 4.7
- Code generation agentFunction calling enables autonomous code workflows
- RAG knowledge assistant1M context ingests large knowledge bases
- Document summarization systemVision + long context for image-heavy documents
GLM-4.5-Air
- Code generation agentFunction calling enables autonomous code workflows
- RAG knowledge assistant128K context for document retrieval
- Customer support automationUltra-low $0.11/1M cost for high-volume tickets
Best For
| Use Case | Claude Opus 4.7 | GLM-4.5-Air |
|---|---|---|
| Coding | ★ | ★ |
| AI Agents | ★★★ | ★★★ |
| Research | ★★★ | ★ |
| Writing | ★★ | ★ |
| Enterprise | ★★★ | ★ |
Performance & Pricing Analysis
On performance, Claude Opus 4.7 leans into 1m context and pairs it with 1M of context — enough for 1m context and strong reasoning. GLM-4.5-Air answers with most affordable glm across 128K, which makes it the stronger fit when you need most affordable glm and good quality. The gap is real, but it's a question of fit rather than dominance.
Pricing is where they part ways. At $5.00/$25.00 versus $0.11/$0.28 per 1M tokens, GLM-4.5-Air is the clear budget pick. Run a typical workload of 1M requests/month at ~1K input / 500 output tokens and GLM-4.5-Air keeps roughly $17250.00/month in your pocket.
Our take: if cost efficiency drives the decision, GLM-4.5-Air wins. Either way, both run through AI API Hub with USDT/USDC payments and instant activation — start with $5 and one API key covers every model.
How to Switch Between Models
Since both Claude Opus 4.7 and GLM-4.5-Air are available through AI API Hub with OpenAI-compatible API format, switching between them requires only changing the model name parameter. Your existing SDK code works without modification.
from openai import OpenAI client = OpenAI(api_key="YOUR_KEY", base_url="https://api.apiyihe.org/v1") # Before: response = client.chat.completions.create(model="claude-opus-4.7", messages=[...]) # After: response = client.chat.completions.create(model="glm-4.5-air", messages=[...])
import OpenAI from "openai";
const client = new OpenAI({apiKey: process.env.KEY, baseURL: "https://api.apiyihe.org/v1"});
// Before: model: "claude-opus-4.7"
// After: model: "glm-4.5-air"curl https://api.apiyihe.org/v1/chat/completions \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"model": "glm-4.5-air", "messages": [{"role":"user","content":"Hello"}]}'💡 AI API Hub supports both models through one API key. No separate accounts needed. Pay with USDT/USDC for all models.
Frequently Asked Questions
What is the difference between Claude Opus 4.7 and GLM-4.5-Air?
They come from different providers and optimize for different things. Claude Opus 4.7 is Anthropic's opus model — 1M context, $5.00/1M input. GLM-4.5-Air is Zhipu AI's glm model — 128K context, $0.11/1M input. The short version: pick based on context size, price, and which capabilities your app actually needs.
Which model is cheaper?
GLM-4.5-Air is cheaper at $0.11/1M input. At typical volumes that difference compounds — run the cost calculator above with your real request count to see the monthly gap.
Which model is better for coding?
Neither is a dedicated coding model. Check the features table above to see what each actually supports.
Which model has a larger context window?
Claude Opus 4.7 wins on context — 1M versus 128K. That matters for long documents, large codebases, or multi-turn conversations that need to stay coherent.
Which model is faster?
GLM-4.5-Air generally responds faster — lighter models tend to have lower latency, though Claude Opus 4.7 may pull ahead on complex reasoning where its larger capacity helps. For latency-critical apps, benchmark both at your real workload.
Which model should I choose?
It depends on your priority. If cost drives the decision, go with GLM-4.5-Air ($0.11/1M). If you need to process long documents or large contexts, Claude Opus 4.7 and its 1M window is the safer bet. If you're building AI agents, both support function calling — pick the cheaper one for volume, the stronger one for quality. When in doubt, start with the cheaper model and upgrade only if quality demands it.
Can both models use function calling?
Yes — both Claude Opus 4.7 and GLM-4.5-Air support function/tool calling, so you can build agents, do structured data extraction, and wire up API integrations with either.
How much does Claude Opus 4.7 cost?
Claude Opus 4.7 runs $5.00/1M input and $25.00/1M output, with 1M of context. It's pay-as-you-go with no minimum — through AI API Hub you can start with $5 and scale up.
How much does GLM-4.5-Air cost?
GLM-4.5-Air runs $0.11/1M input and $0.28/1M output, with 128K of context. It's pay-as-you-go with no minimum — through AI API Hub you can start with $5 and scale up.
Which model is better for enterprise use?
Claude Opus 4.7 sits in the premium tier and is built for demanding workloads, but either can serve enterprise needs — weigh your security, compliance, and throughput requirements.
Which model is better for AI agents?
Both handle tool calling, so either works for agents. For high-volume agent calls, GLM-4.5-Air keeps costs down; for complex multi-step reasoning, the pricier model may reason more reliably.
How do I access these APIs?
Both run through AI API Hub on one OpenAI-compatible endpoint. Register at api.apiyihe.org, deposit USDT or USDC (no credit card), grab your API key, and call https://api.apiyihe.org/v1 with model name "claude-opus-4.7" or "glm-4.5-air". One key unlocks every model.
Can I switch between these models without changing my code?
Yes — because AI API Hub is OpenAI-compatible, moving from Claude Opus 4.7 to GLM-4.5-Air (or back) is just a model-name change. Your SDK setup, message format, and streaming logic stay exactly the same.
Final Verdict: Which Should You Buy?
💰 Cheapest pricing · ⚡ Instant API key · 🚫 No credit card · 💎 Pay with USDT/USDC · 🔌 OpenAI-compatible
Conclusion: GLM-4.5-Air is the cheaper choice — save $17250.00/month (99%) at your volume. Buy GLM-4.5-Air API for the cheapest pricing and instant API key.
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Access Claude Opus 4.7 & GLM-4.5-Air via AI API Hub
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