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Model comparison · accepted catalogue facts 2026-09-23

Claude Opus 4.6 vs MiniMax M2.7

Neither model has both an equal-or-higher measured score and an equal-or-lower estimated price in this pair. Retaining your current model is a valid outcome.

Observed search question: “minimax m2.7 vs opus 4.6” · 2026-09-09

Claude Opus 4.6

LMArena general · Elo · higher is better

Scale starts at 1040 Elo

1503.0

Balanced effective USD / 1M tokens · lower is better

$10.00/M

MiniMax M2.7

LMArena general · Elo · higher is better

Scale starts at 1040 Elo

1404.6

Balanced effective USD / 1M tokens · lower is better

$0.525/M

Compare · model decision

Choose two or three models

Inspect the differences, estimate your workload and keep the evidence. All standard catalogue models are available, including unrated ones.

Catalogue facts
2026-09-23

2 / 3 selected · 0 requirements
Open public comparison link
Public workload and requirements

These settings are included in the share link. The fixed-request scenario and private evaluation data below are excluded.

A ↔ B

Neither model has both an equal-or-higher measured score and an equal-or-lower estimated price in this pair. Retaining your current model is a valid outcome.

Estimated blend: 75% input, 25% output; 0% cached input. Base context tier. Prompt length selects the billing tier. An unlisted cache-read rate uses that tier’s full input rate in this blend; missing required input or output rates prevent an estimate. The fixed-request estimate below validates actual context and output limits and requires a published cache-read rate when cache hits are assumed.

What changes between these models

Quality first, then estimated price. LMArena scores are human-preference measurements, not a benchmark of your application. A missing score is unrated.

  • Claude Opus 4.6 · Meets the stated model requirements
  • MiniMax M2.7 · Meets the stated model requirements
Material differences and unknown evidence. Deltas compare each model with model A. Unknown facts remain visible.
Measured factA Claude Opus 4.6B MiniMax M2.7
LMArena general score (Elo)1,5031,404.6Δ vs A: -98.4 Elo
Score interval half-width (± Elo)3.493.58Δ vs A: +0.09 Elo
Benchmark reasoning efforthighdefault
LMArena document score (Elo)1,507.3Unknown
Estimated effective USD / 1M tokens$10$0.525Δ vs A: -9.475 USD/M
Base input USD / 1M tokens$5$0.3Δ vs A: -4.7 USD/M
Base output USD / 1M tokens$25$1.2Δ vs A: -23.8 USD/M
Base cached-input USD / 1M tokens$0.5$0.06Δ vs A: -0.44 USD/M
Context window (tokens)1,000,000204,800Δ vs A: -795,200 tokens
Output limit (tokens)128,000131,072Δ vs A: +3,072 tokens
Input modalitiestext, image, filetext
Open weightsNot supportedUnknown
Recorded licenceproprietaryUnknown
Model providerAnthropicMiniMax
Distinct sellers in the catalogue58Δ vs A: +3
Serving precision differs across offersNot supportedSupportedΔ vs A: +1
Recorded retirement dateUnknownUnknown
3 shared measured facts
Shared measured facts. Deltas compare each model with model A. Unknown facts remain visible.
Measured factA Claude Opus 4.6B MiniMax M2.7
Tool useSupportedSupportedΔ vs A: 0
ReasoningSupportedSupportedΔ vs A: 0
Retirement evidenceNone announced; not a guaranteeNone announced; not a guarantee

Provider counts and precision flags describe catalogue offers. They do not establish the precision, availability, region, tool behaviour or limits of your chosen endpoint. Open each model’s provider table before switching.

Complete price ladders and billing conditions

Claude Opus 4.6

Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.

Input-token thresholdInputOutputCached input
Base, up to and including first threshold$5$25$0.5

MiniMax M2.7

Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.

Input-token thresholdInputOutputCached input
Base, up to and including first threshold$0.3$1.2$0.06
Migration preflight · compare each candidate with model A

Keeping Claude Opus 4.6 is a valid decision. No pairwise comparison certifies a drop-in replacement.

Claude Opus 4.6 → MiniMax M2.7

Known loss or failed requirement

  • Context window: 1,000,000 → 204,800 tokens.
  • image input is not supported by the candidate.
  • file input is not supported by the candidate.
  • Provider endpoint, serving precision, availability and task success need your own verification. Catalogue model capabilities do not certify an endpoint.
Check alternatives to Claude Opus 4.6

Estimate a fixed request shape

Private to this tab unless you save locally or explicitly export private details. These are estimates, not observed invoices. Cross-model token counts and task success are assumptions.

0.1 extra attempts means 10 extra full attempts per 100 requests. Cache writes, tool charges, taxes and unlisted charges are excluded.

  • Claude Opus 4.6Estimated total: $22.5 1,000 full attempts · base rates
  • MiniMax M2.7Estimated total: $1.2 1,000 full attempts · base rates
Prompt and output sensitivity · sampled scenarios

Every point recalculates the entire request shape. Tier-boundary samples include one token below, at and above each threshold. Ordering between samples is not guaranteed. Lowest known cost excludes unknown estimates and is not a replacement recommendation.

Vary input; hold output, requests, cache and retries fixed.
Input tokensClaude Opus 4.6MiniMax M2.7Coverage
2,000$22.5$1.2Lowest knownAll computed
4,096$32.98$1.8288Lowest knownAll computed
32,768$176.34$10.4304Lowest knownAll computed
131,072$667.86$39.9216Lowest knownAll computed
Vary output; hold input, requests, cache and retries fixed.
Output tokensClaude Opus 4.6MiniMax M2.7
128$13.2$0.7536
2,048$61.2$3.0576
8,192$214.8$10.4304

Bring your observed evaluation results

JSON is parsed locally. Prompts, filenames, individual responses and extra fields are not retained. Import only aggregate measurements for selected models. Task/version labels do not establish that two evaluations used the same dataset.

Expected format
[{"model":"provider/exact-model-id","task":"support-answer","version":"rubric-1","attempts":100,"successes":84,"costUsd":2.4,"latencyMs":950}]

Use the exact catalogue ID. Replace the example values with observed measurements. Omit costUsd or latencyMs when they are unknown. No public score is inferred from these observations.

Keep the decision and its evidence

A portable record retains selected facts, complete tier ladders, public requirements and the publication manifest. It also embeds the full permitted public catalogue to verify the input artifact checksum. Files are larger for this reason (up to 2 MB); local storage is limited to 12 records. Team review is local to this browser; there is no hosted collaboration.

Saving is opt-in and includes private review fields. Shared comparison links never include them. Version 1 Check references remain separate and are not overwritten or guessed into this format.

Saved local decisions · 0

No version 2 decision records are stored in this browser.

Questions this page answers

Is Claude Opus 4.6 a better-and-cheaper replacement for MiniMax M2.7?

Neither model has both an equal-or-higher measured score and an equal-or-lower estimated price in this pair. Retaining your current model is a valid outcome.

What is included in this comparison?

Accepted model capabilities, context and output limits, complete price-tier ladders, independent LMArena measurements and missing evidence. Provider endpoint precision and application success still need verification.

Can I compare a different workload or keep a decision record?

Yes. Change the public workload, prompt length and requirements in the comparison workspace. Fixed-request scenarios, aggregate evaluations and review notes stay local unless explicitly exported.

Evidence & Ask