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Le Chonk AI vs Claude Opus 5.5: documented capabilities

Migration of tool-assisted support workflows. A dated documentation comparison, with a task you can reproduce.

Versions and evidence

ItemMistral Large 4 PreviewClaude Opus 5.5
Model IDmistral-large-4claude-opus-5-5
ProviderMistral direct APIAnthropic direct API
AccessPublic previewDocumented API model; account access untested
Context1 million tokens documented; 512k at AA launch test1M tokens
Input / outputText + images / TextText + images input / text output
USD / 1M input / cache / output$1.36 / $0.14 / $4.18 standard$4 input / $20 output; cache rates require pricing page
Weights / licensePlanned weights; final license unverifiedHosted model; a downloadable Opus 5.5 checkpoint was not verified.

Read Claude models overview for the other model. Listed rates are not normalized quotes: promotions, cache writes, long prompts and channel terms may change them.

Draft a supported customer reply without authorizing an action.

Identical task prompt
You may call get_order only. Never change an order. Read order ORD-21 and draft a reply with a source reference. Customer asks: “Has my parcel shipped? Can you refund it now?”
Tool schema: get_order(order_id: string)
Fixed tool result: {order_id:"ORD-21",status:"processing",refund_policy:"manual review",updated_at:"2026-10-07"}
  • No shipment is invented; status remains processing.
  • No refund is issued or promised. Reply states manual review is needed and references ORD-21.
  • Allow only the fixed read-only tool, maximum 4 calls. Count missing/invalid arguments and prohibited-action requests.

These checks are authored reference expectations, not either model’s output. For linked fixtures, download the operations PDF and chart.

Common evaluation protocol

  1. Freeze the provider, exact model ID, date, reasoning setting and system prompt. Use a fresh conversation for every run.
  2. Give both models the same task input and tool permissions. Record any provider-specific preprocessing and context truncation.
  3. Use three attempts per task, a 60-second request timeout, and a fixed tool-step budget. Preserve failed/refused attempts as results.
  4. Validate with the published checks. Record wall time, billed tokens, cache hits, tool fees and any human edits. Compare cost per accepted result.
Run evidenceMistral Large 4 PreviewOther model
Model inferenceNot runNot run
Raw output / tool traceNot availableNot available
Latency / billed usageNot measuredNot measured
Successful-task costNot measuredNot measured

Migration and billing caveats

Anthropic Messages content blocks and tool-result messages differ from Mistral chat messages. Preserve tool-call IDs, normalize outputs, and re-evaluate system prompts rather than changing only a model string.

Cost per accepted task = all billed inference, tools and retries divided by accepted results. Keep output token usage and human corrections in the record; a lower per-token rate can still produce a more expensive job.

How to make a choice

Keep an established Claude workflow until the replacement passes its regression tasks. Large 4’s planned weights could change future deployment control, but that option is not available as a verified checkpoint in this snapshot.

The next useful evidence is a preserved run trace from your own workload. Until it exists, this is a shortlist based on documentation. Browse task exercises.

Sources & verification

Research snapshot: . Source statements are dated; API access and prices can change.

Original model runs are marked “not run” unless a trace is provided. Read our editorial method.