Claude Opus 5: Benchmarks, Pricing & Full Guide (Opus 4.8 Focus)

Claude Opus 5 and Opus 4.8: Same Brains, Same Official Price

Claude Opus 5 is here, and according to Coursiv's detailed breakdown, it carries the exact same API pricing as its predecessor: $5 per million input tokens and $25 per million output tokens. Yes — you read that right. The official price of Opus 4.8 was also $5/$25.

But here's the thing most pricing guides miss: the price you pay for Claude Opus depends on where you access it. On OneMux, Claude Opus 4.8 is available for just $1.5 per million input tokens and $7.5 per million output tokens — a 70% reduction on the official rate. That's not a temporary promotional discount; it's how OneMux's pay-as-you-go model works: you only pay for what you use, and the infrastructure savings are passed down.

Takeaway: If you're building on Claude Opus, the OneMux route turns a $25 output token into $7.50. For teams processing millions of tokens a day, that's a serious line-item change.

Why Claude API Pricing Matters for Developers

The Claude API pricing model heavily weights output tokens — they are five times more expensive than input tokens in the official plans. That means any application that generates long responses (e.g., code generation, report writing, or chat agents) is going to burn through budget quickly.

Let's make this concrete. Suppose you have a support bot that sends 50,000 tokens per user query (10K input + 40K output). With official Claude Opus 4.8 pricing:

input_tokens = 10_000
output_tokens = 40_000
input_price_per_million = 5   # dollars
output_price_per_million = 25 # dollars

cost_per_query = (input_tokens/1_000_000 * input_price_per_million) + (output_tokens/1_000_000 * output_price_per_million)
print(f"Cost per query: ${cost_per_query:.2f}")

That script would output $1.05 per query. Now run the same calculation with OneMux's Opus 4.8 pricing ($1.5/$7.5):

input_price_per_million = 1.5
output_price_per_million = 7.5

cost_per_query_onemux = (input_tokens/1_000_000 * input_price_per_million) + (output_tokens/1_000_000 * output_price_per_million)
print(f"Cost per query via OneMux: ${cost_per_query_onemux:.2f}")

That's just $0.315 per query. Multiply by a million queries and you've saved almost $735,000. The pricing angle isn't a footnote—it's the whole story.

GPT-5.6 API: How It Stacks Up

The "GPT-5.6 API" isn't a single model—it's a family. On OneMux, you can access three variants: GPT-5.6 Terra, GPT-5.6 Luna, and GPT-5.6 Sol. Each is priced differently, and the one you choose should depend on the task.

Here's the complete OneMux price list for the models we're discussing:

According to the Coursiv article on Claude Opus 5, the official GPT-5.6 Sol API pricing is $5 per million input and $30 per million output, and it leads most benchmarks they tested. On OneMux, the same GPT-5.6 Sol costs $2.5 per million input and $15 per million output — again, 50% off the official rate. But "leads most benchmarks" doesn't mean "best at everything." Let's look at when to reach for which.

Choosing the Right Model: Claude Opus 4.8 vs. GPT-5.6 Variants

When Claude Opus 4.8 is the smarter pick

Claude Opus models shine at long-context reasoning, nuanced writing, and following complex instructions with a specific voice. If your app needs to read a 50-page contract or generate a coherent multi-threaded narrative, Opus 4.8 will feel more "aligned" than many alternatives. The fact that OneMux prices it at the same rate as the older Opus 4.7 makes it a no-brainer for production workloads.

When to switch to GPT-5.6 Sol

If your benchmark tests are the decisive factor—and they should be for things like math, code, or agentic tool use—GPT-5.6 Sol appears to edge out Claude Opus 4.8 in most of Coursiv's tests. With OneMux pricing at $2.5/$15 per million tokens, Sol is 66% more expensive on input and 2x more expensive on output than Opus 4.8 on OneMux. That premium might be worth it if you're shipping a coding assistant where accuracy is the #1 KPI.

When to use GPT-5.6 Luna or Terra

Luna is a genuinely cheap request: $0.6/$3.6 per million tokens. It's perfect for high-volume classification, summarization of short text, or first-pass draft generation. Terra acts as a mid-tier option, priced identically to Opus 4.8 on input ($1.5) but with $9 output. Use Terra for simple chat assistants that need more OpenAI-style formatting but don't need Sol's heavy reasoning.

How to Set Up Claude Opus 4.8 on OneMux

OneMux exposes every model through an OpenAI-compatible API, so you can switch between Claude and GPT using the same SDKs, libraries, and environment variables.

Here's a minimal Python example using the openai library

from openai import OpenAI

client = OpenAI(
    api_key="your-onemux-api-key",
    base_url="https://your-onemux-endpoint.com/v1"  # Replace with the URL from OneMux docs
)

response = client.chat.completions.create(
    model="claude-opus-4.8",
    messages=[
        {"role": "system", "content": "You are a pricing analyst."},
        {"role": "user", "content": "Explain the cost difference between input and output tokens."}
    ]
)

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

Note: the exact base URL and model name format can be found in the OneMux quickstart guide. Don't guess—check the docs.

Cost Optimization Tactics with OneMux

Claude API pricing doesn't have to be unpredictable. Here's how to stay in control:

1. Set a default model group. Route simple prompts to GPT-5.6 Luna, complex tasks to Opus 4.8. OneMux's model routing means you classify the input and let the API pick the best-cost model.
2. Watch output tokens. Since output tokens cost 5x input tokens, structure your prompts to request shorter responses, use JSON mode for constrained formats, and cap max_tokens.
3. Review spend on the dashboard. OneMux gives you per-request spend visibility, so you can catch cost spikes before they hit the invoice. See the OneMux model catalogue and pricing page for details.

Conclusion

Claude Opus 5 and Opus 4.8 share the same official $5/$25 per million token price, but adding OneMux into the mix rewrites the cost equation. Claude Opus 4.8 on OneMux delivers Opus-level reasoning at $1.5/$7.5 per million tokens, while GPT-5.6 Sol gives you a strong benchmark alternative at $2.5/$15. Neither price appears in the official press releases, which is exactly why you need a routing layer that aggregates model access and pricing in one place.

If you're ready to build, start with the OneMux quickstart, review the full model list, and don't forget to check the API documentation for more advanced usage.

FAQ

Is Claude Opus 5 available on OneMux?

OneMux currently offers Claude Opus 4.8 and 4.7. The source we cite indicates Opus 5 shares the same official pricing as Opus 4.8, but for the best value today, Opus 4.8 on OneMux is the cost-effective choice.

How does Claude Opus 4.8 compare to GPT-5.6 Sol on price?

On OneMux, Claude Opus 4.8 costs $1.5/$7.5 per million tokens, while GPT-5.6 Sol costs $2.5/$15. In official pricing, the gap is $5/$25 vs $5/$30 — so Opus is more affordable on output tokens in both cases.

Can I use OpenAI SDKs with Claude Opus through OneMux?

Yes. OneMux provides an OpenAI-compatible base URL, so you can use the openai Python library or any other OpenAI SDK to call Claude Opus 4.8. Just set the model name to the OneMux identifier for Claude Opus 4.8.

What is the difference between GPT-5.6 Luna and GPT-5.6 Sol?

Luna is a budget model ($0.6/$3.6) designed for high-speed, high-volume tasks. Sol is the flagship model ($2.5/$15) that leads in benchmark testing, making it a better fit for complex reasoning and code generation.

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Sources

• Claude Opus 5 on Coursiv — Used for official pricing of Claude Opus 5/4.8 and GPT-5.6 Sol, and benchmark leadership claims.
• OneMux Model Catalogue — OneMux's current model list and pricing.
• OneMux Pricing — OneMux's pricing model explanation.