OpenRouter 实测 Claude Opus 5.5、Sonnet 5.5 与 Haiku 5.5 该怎么选

Use Claude Sonnet 5.5 as your default, Claude Haiku 5.5 for high-volume and sub-agent work, and Claude Opus 5.5 when a task is long, ambiguous, or expensive to get wrong.

For most teams, the choice is between Opus and Sonnet, and the question is whether Opus is worth twice Sonnet’s price per token. On the coding tasks we tested, it wasn’t. We gave each model the same 11 coding tasks with hidden tests and the same bug-fix task in Claude Code. Every model passed everything, so what separated them was cost. Haiku was 19 to 30 times cheaper than Opus per task, and Sonnet cost between half and two-thirds as much as Opus.

Those results tell you how the three did on our tasks. The only way to know which one is best for your workflow is to test them on your own work. Ori Eval does this for you. You ask your coding agent which model is best for your project, and it finds test material in your code, writes the eval, runs the models you want to compare, and recommends one with the scores, times, and costs behind it. The section on switching between them shows how to point it at all three tiers.

Tl;dr

• Use Claude Sonnet 5.5 as your default. It scored as well as or better than Opus 5.5 on our GPQA Diamond and τ-bench runs and passed every coding test, at half the per-token price.
• Use Haiku 5.5 for high-volume and sub-agent work. It passed every coding test too, at a 12th to a 16th of Sonnet’s cost.
• Keep Opus 5.5 for long, ambiguous tasks where a mistake costs more than the tokens. Our short tasks can’t rule out an advantage there.
• Our tasks aren’t yours. Test the three on your own work with Ori Eval before you settle on one.
• All three are one model string apart on OpenRouter, and Claude Code can use a different one for each role.

How do Opus, Sonnet, and Haiku differ?

Opus 5.5, Sonnet 5.5, and Haiku 5.5 are three tiers of the same model generation. Anthropic released Opus 5.5 on September 22, 2026, Sonnet 5.5 on September 28, and Haiku 5.5 on October 7. All three have a 1-million-token context window and accept text, images, and PDFs. They differ mostly in price and, for Haiku, in lower benchmark scores.

Prices are our list prices on October 21, 2026, from the model pages for Opus 5.5, Sonnet 5.5, and Haiku 5.5. The benchmark rows come from our benchmarks endpoint, pulled on October 21 (our runs of October 17). The Artificial Analysis Intelligence Index is a composite score across 10 evaluations from the independent benchmarking firm Artificial Analysis. T means trillions of tokens, from our daily rankings dataset.

Is Opus better than Sonnet?

On the benchmarks we run, Claude Opus 5.5 does not beat Claude Sonnet 5.5. Sonnet scored higher on our run of GPQA Diamond, a set of 198 graduate-level science questions (92.4% vs 90.4%). It also scored higher on τ-bench airline, a multi-turn customer-service agent benchmark (78.7% vs 75.5%). Opus leads by 1.6 points on the Artificial Analysis index. On both of our runs, Sonnet costs less than half as much per task, at $0.025 per GPQA question against $0.054 and $0.16 per τ-bench task against $0.34.

In the week of October 12, Opus 5.5 carried about two and a half times Sonnet’s token volume on OpenRouter. Opus is also Claude Code’s default model on most plans, and in our test Claude Code used Opus 5.5 through OpenRouter when no model was set. If you haven’t changed your model, Opus is what you’re running.

Is Haiku good enough to replace Sonnet?

Haiku 5.5 can replace Sonnet for well-specified, routine work. It scored 76.0% on τ-bench airline, half a point above Opus and 2.7 points behind Sonnet, at $0.011 per task. That is about a fourteenth of Sonnet’s cost. Our runs had 100 to 200 tasks per model, so gaps of a few points on this benchmark may be noise. Haiku trails Sonnet by 5.8 points on GPQA Diamond and by 12.6 points on the Artificial Analysis index, which weights agentic tasks and general knowledge at 30% each and coding and scientific reasoning at 20% each. On routine coding, our tests below found no gap.

What did our coding tests show?

We tested two things, writing a function to a spec and fixing a repo with Claude Code. All three models passed every test in both.

Functions with hidden tests

We wrote 11 Python tasks, each with a hidden test file. The eight everyday tasks were parsing durations, merging intervals, an LRU cache, an arithmetic evaluator without eval, the next run time of a cron expression, word wrapping, Semantic Versioning sort order, and a JSON path reader. The three hard tasks were a regex engine without the re module, a SQL WHERE filter with three-valued NULL logic, and free calendar slots across time zones on daylight-saving transition days. Each model answered each everyday task twice and each hard task three times, with the models’ default settings, for 25 attempts per model.

Haiku used the most reasoning and still finished the hard tasks fastest. On the hard tasks it used 3,202 reasoning tokens on average, against 1,252 for Opus. Reasoning tokens are the tokens a model spends working through a problem before it writes its answer. Even with the extra reasoning, Haiku cost a 27th as much as Opus per hard task.

A bug-fix in Claude Code

We gave Claude Code a small invoicing library with three bugs and five tests. The bugs were rounding that used banker’s rounding (round half to even), a CSV parser that split on commas inside quotes, and a summary that overwrote quantities instead of adding them. We ran it three times per model through OpenRouter, choosing the model with the ANTHROPIC_MODEL environment variable.

A turn is one model response in the session. We computed session cost from each session’s token counts at our prices, because Claude Code’s own figure was wrong for Haiku.

Claude Code’s own total_cost_usd field didn’t recognize our Haiku slug and reported $0.16 to $0.31 per session, 30 to 60 times our computed median of $0.0052. In print mode (claude -p), Claude Code logs a warning when it doesn’t recognize a model slug. We saw it again on a one-word reply through Haiku, where Claude Code reported $0.107 and the request cost about $0.002 at our prices.

[claude-code:unrecognized_model] {"model":"anthropic/claude-haiku-5.5","query_source":"sdk"}

If you run Claude Code through OpenRouter, check spend on your Activity page instead, and use our spend controls if you need a cap.

These are small, well-specified tasks. On these tasks, the three tiers were equally reliable, and their costs differed widely. They don’t cover the work Anthropic built Opus for, which is long-running agentic coding and knowledge work where a mistake costs more than the tokens.

Which one should you use?

• If you want one default, use Claude Sonnet 5.5. It scored as well as or better than Opus on both of our benchmark runs and matched it on all of our tests, at half the per-token price.
• If you run a lot of requests, such as classification, extraction, sub-agents, or bulk code edits, use Haiku 5.5. It passed every test we gave it at a 12th to a 16th of Sonnet’s cost and a 19th to a 30th of Opus’s. Keep prompts under 100,000 tokens to stay on its lower price. Outside Claude Code, our Subagent server tool lets a larger model hand self-contained tasks to a smaller one.
• Use Opus 5.5 for long tasks where a mistake is costly. That is the work it is built for, and our short tasks can’t rule out an advantage there.
• If you can’t tell which group your workload is in, test your own tasks rather than ours, as described in the next section.

How do you switch between them?

We serve all three models through one API, one key, and one request format, so switching means changing the model string. This loop sends the same prompt to each tier and prints the output tokens and the cost we return on every response.

import os
import requests
for model in ["anthropic/claude-opus-5.5", "anthropic/claude-sonnet-5.5", "anthropic/claude-haiku-5.5"]:
    r = requests.post(
        "https://openrouter.ai/api/v1/chat/completions",
        headers={"Authorization": f"Bearer {os.environ['OPENROUTER_API_KEY']}"},
        json={"model": model, "messages": [{"role": "user", "content": "Write a Python function that merges overlapping intervals."}]},
        timeout=300,
    )
    usage = r.json()["usage"]
    print(f"{model}: {usage['completion_tokens']} output tokens, ${usage['cost']:.4f}")

This is the output from our run on October 13, 2026.

anthropic/claude-opus-5.5: 1190 output tokens, $0.0239
anthropic/claude-sonnet-5.5: 876 output tokens, $0.0088
anthropic/claude-haiku-5.5: 852 output tokens, $0.0004

Run your own tasks through each tier with Ori Eval. Ori Eval tests are TypeScript *.eval.ts files. Pass each of the three slugs to setupAgent({ model }) in one file, and the same tests run on every tier.

In Claude Code, you can keep Opus for planning and send routine work to cheaper models. Point Claude Code at OpenRouter with our setup guide, then set the model for each role.

export ANTHROPIC_DEFAULT_OPUS_MODEL="anthropic/claude-opus-5.5"
export ANTHROPIC_DEFAULT_SONNET_MODEL="anthropic/claude-sonnet-5.5"
export ANTHROPIC_DEFAULT_HAIKU_MODEL="anthropic/claude-haiku-5.5"
export CLAUDE_CODE_SUBAGENT_MODEL="anthropic/claude-haiku-5.5"

Claude Code 2.1.307 recognizes the Opus and Sonnet slugs and gives them their 1-million-token context window. It doesn’t recognize the Haiku slug yet and assumes 200,000 tokens. To give Haiku its full window, add [1m] to its slug. We strip the suffix before routing. Leaving it off keeps Haiku sessions under about 200,000 tokens.

These variables set which model each name points to. They don’t change which one you use. To make Sonnet your main model, run /model sonnet in a session or set ANTHROPIC_MODEL=sonnet before you start Claude Code. To plan with Opus and write code with Sonnet, run /model opusplan instead. Because CLAUDE_CODE_SUBAGENT_MODEL is set, sub-agents that don’t name their own model run on Haiku.

If you’d rather have us pick per request, the Auto Router (openrouter/auto) chooses a model for each prompt. For coding, the Pareto Router picks a model that meets a minimum coding score you set.

Frequently asked questions

Is Claude Haiku cheaper than Sonnet?

Yes. On OpenRouter, Haiku 5.5 costs 20 times less per input and output token than Claude Sonnet 5.5 for prompts under 100,000 tokens, at $0.10 per million input tokens against $2.00. In our Claude Code runs the gap per session was smaller, about 12 times, partly because Haiku took more turns to reach the same result.

Is Sonnet 5.5 better than Opus 5.5 for coding?

In our Claude Sonnet vs Opus coding tests, the two were equal. Both passed all 25 hidden-test attempts and all three Claude Code runs through OpenRouter, and Sonnet was faster and cost half to two-thirds as much. Opus leads by 1.6 points on the Artificial Analysis index, and Anthropic positions it for long-running agentic coding, so it’s the safer choice for long, ambiguous sessions.

What is Claude Haiku good for?

Haiku 5.5 is good for high-volume, well-specified work such as classification, extraction, routing, sub-agent tasks, and routine code changes. In our tests through OpenRouter it passed every coding task, including a regex engine and SQL three-valued NULL logic, and scored half a point above Opus on τ-bench airline.

Which Claude model does Claude Code use?

Claude Code uses Opus 5.5 by default on Pro, Max, Team, Enterprise, and Anthropic API accounts, according to Anthropic’s model configuration docs. When you run Claude Code through OpenRouter, you can change the main model with ANTHROPIC_MODEL and set each role with the environment variables above.

Next steps

• Ori Eval runs Opus, Sonnet, and Haiku on your own tasks and recommends one. To start, give your coding agent this instruction: run curl -fsSL https://openrouter.ai/skills/spawn-ori-eval and follow the instructions in its output to get started.
• Our setup guide covers per-role model settings, and our tutorial Claude Code with OpenRouter: Setup, Models, and Costs covers model choice and costs.
• The model pages for Opus 5.5, Sonnet 5.5, and Haiku 5.5 show current prices, providers, and uptime. Our Opus 5.5 vs Sonnet 5.5 comparison page puts two of them side by side.
• Prompt caching explains the cache-read prices in the table above.
• The Claude 5.5 migration guide covers the API changes if you’re moving from an older Claude model.
• Cost vs. Quality Tradeoff Framework for Agent Models and Confidence Thresholds for Model Escalation Routing cover when to move a request up a tier.