Claude Opus 5.5 vs GPT-6.1 Sol for coding agents

Originally published on the QuickSilver Pro blog.

On QuickSilver Pro, Claude Opus 5.5 costs $1.00 / $5.00 per million tokens and GPT-6.1 Sol costs $2.00 / $10.00. Both are sold for agentic coding, so for anyone running a coding agent the question is which one gets the work done, how fast, and for how much.

We tested this on 2026-10-27. Both models ran in the same agent, OpenCode, on six small but real coding tasks, and we graded every run with tests the agent never saw. Short answer: both models passed every hidden test in every run. Opus finished a task in 82 seconds on average and Sol in 152. Per task they cost about the same: $0.094 for Opus and $0.098 for Sol.

opencode run --auto), with QuickSilver Pro added as an OpenAI-compatible provider. The only thing that changed between runs was -m quicksilverpro/claude-opus-5-5 or -m quicksilverpro/gpt-6.1-sol. We could not use Claude Code here. QuickSilver Pro serves GPT-6.1 Sol only on the OpenAI-compatible endpoints (/v1/chat/completions and /v1/responses), and Claude Code needs the Anthropic Messages API, so we used one agent that can drive both models.edit / write tools. With Sol it used a 5,100-character prompt and an apply_patch tool. Each model therefore ran the way OpenCode normally drives it. The tasks:

"1h30m", "2 hours and 5 min", "PT1H30M") with a page of rules on separators, unit order and what must be rejected, including non-ASCII digits. 84 hidden tests.${section.key} references with cycle detection. 57 hidden tests. Averages over two runs per model and task. Cost is per run, at QuickSilver Pro prices on 2026-10-27.

Where the tokens and the money went, averaged over all 12 runs per model:

Sol's uncached-input line includes cache writes: QuickSilver Pro billed some of Sol's uncached input at the cache-write rate rather than the plain input rate. Opus's uncached input was billed at the plain input rate.

Quality was a tie. Neither model failed a hidden test in 24 runs. That includes all 136 cases of the official Mustache suite and the 316 comparisons with the original function in the refactor. These tasks did not find a ceiling for either model.

Opus was faster on every task. On average Sol took 1.9 times as long, from 1.5 times as long on the Mustache renderer to 4 times as long on the bug fix. Two things account for it. Opus used fewer requests per task (7.9 against 12.1), so it made fewer round trips. Its requests were also quicker, with a median of 7.6 seconds per request against 11.7 for Sol. Sol also split its work into more small steps. Over 12 runs it made 54 calls to OpenCode's file-read tool and 43 to-do-list updates. Opus made 6 and none.

The cost came out even, for two different reasons. Opus has the lower per-token prices, but it wrote almost twice as much output (7,800 tokens per task against 4,200). It also got less of its input from the prompt cache. On every Opus request the cache covered the same 8,028 tokens, about the size of OpenCode's system prompt and tool definitions. The rest of the conversation was billed at the full input rate each time. Sol's cache hits grew with the conversation and covered 81% of its input. Sol was cheaper on the two longest tasks, the config parser and the Mustache renderer. Opus was cheaper on the other four.

Both checked their own work the same way. In both refactor runs, each model saved a copy of the original function and wrote a throwaway script that compared old and new output on random inputs. On the Mustache task, both models downloaded the official spec test files from GitHub in both runs and ran them before finishing: Opus with curl, Sol with OpenCode's web-fetch tool and a Python one-liner. Our hidden tests for that task are the same files, so neither model's Mustache score is independent of what it downloaded.

Opus 5.5 is the better default for interactive work on tasks like these. You wait about half as long for the same result, at the same price per task.

GPT-6.1 Sol is just as good at these tasks and was the cheaper of the two on the two longest ones. If your agent runs unattended and wall time matters less than the bill, the two are close enough that your own workload should decide. We did not find a task in this set that either model failed, so we cannot tell you which one solves more on harder work.

Both models are on the same QuickSilver Pro key and balance, so trying the other one is a change of -m.

The OpenCode config we used, pointed at the public endpoint. Save it as opencode.json in your project:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "quicksilverpro": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "QuickSilver Pro",
      "options": {
        "baseURL": "https://api.quicksilverpro.io/v1",
        "apiKey": "{env:QSP_API_KEY}"
      },
      "models": {
        "claude-opus-5-5": { "name": "Claude Opus 5.5", "limit": { "context": 1000000, "output": 64000 } },
        "gpt-6.1-sol": { "name": "GPT-6.1 Sol", "limit": { "context": 1000000, "output": 64000 } }
      }
    }
  }
}

Then run the same prompt with each model:

export QSP_API_KEY=YOUR_QSP_KEY

opencode run --auto -m quicksilverpro/claude-opus-5-5 "Fix the failing test in tests/"
opencode run --auto -m quicksilverpro/gpt-6.1-sol "Fix the failing test in tests/"

--auto approves the agent's file edits and shell commands without asking, so use it only in a project you can reset. OpenCode shows a cost of 0 for a custom provider. The real cost of each request, with its model and token counts, is in your QuickSilver Pro dashboard. For more on the setup, see Use QuickSilver Pro in OpenCode and Crush. For the same six-task method with Claude Code, see Claude Opus 5.5 vs Sonnet 5.5 for coding agents. Claude Opus 5.5 is 75% below Anthropic's list price of $4.00 / $20.00.