ModelSpec is an analysis of alternatives for AI models: it decides which models fit a job from your requirements, sourced benchmarks and real cost, and shows its work.
Claude Opus 5.5 vs Grok 4.7 for General assistant (balanced), as of 2026-09-23
Find an active assistant that balances how people rate its responses against task cost.
Worked example as of 2026-09-23, from the public data image.
What the evidence says
The evidence can't separate them for this job.
Grok 4.7 has a 26% chance of matching or beating Claude Opus 5.5 on this job's objective.
probability bands: a model joins the leader when P(its score >= the leader's) >= 0.25 under the score posteriors; a weighted capability with an 80% interval wider than 2.8 is not enough evidence
Decision status: partial. P(best) and score intervals retain the full ranked lineup for this job, including models beyond this pair and models with thin evidence. Models with unknown objective values remain unranked and are outside this probability. P(best) is not a head-to-head probability.
Scores and score intervals use the objective's dimensionless normalised units. Cost per task is in USD for the selected offering and the applied spec's task size. When task size is omitted, the engine uses its documented default. Unavailable means the engine returned no value.
| Model | Score | Score interval | P(best), ranked job lineup | Cost per task, USD | Selected offering: provider / region / tier | Capability estimates and intervals |
|---|---|---|---|---|---|---|
| Claude Opus 5.5 | 0.846914 | [0.703041, 0.990787] | 41% | 0.24 | anthropic / global / standard |
|
| Grok 4.7 | 0.745338 | [0.601465, 0.889211] | 7% | 0.104 | xai / global / standard |
|
Response quality first, cost as a real second term.
Requirements
model.class = text-generator: A conversational assistant needs a text-generating model.model.lifecycle = active: An active model is still supported by its lab or provider.
Preferences
chat_preference: Prefer assistants whose open-ended responses people rate more highly.-offering.cost_per_task: Among strong assistants, prefer the cheaper task.
Applied template spec
spec_version- 1
where- model.class = text-generator
- model.lifecycle = active
optimizeweightschat_preference- 0.6
-offering.cost_per_task- 0.4
Evidence for Claude Opus 5.5
| Benchmark | Version | Measurement | Unit | Published interval | Evidence date | Measurement conditions | Provenance |
|---|---|---|---|---|---|---|---|
| arena_webdev | webdev / overall, latest split, revision 1880dbebff5b | 1818.41 | Arena score (Elo scale) | Unavailable | 2026-09-23 |
| Source |
Missing facts for Claude Opus 5.5
model.hardware_fit_indeterminate: unknownmodel.languages: unknownmodel.parameters_total: unknownorigin.base_lineage: not_disclosedorigin.weights_hosting: not_disclosedoffering.api_model_id: unknownoffering.data.zero_retention: requires_contractoffering.private_deployment: unknownoffering.router_slug: unknownoffering.speed.throughput: unknownoffering.speed.time_to_first_token: unknown
Evidence for Grok 4.7
| Benchmark | Version | Measurement | Unit | Published interval | Evidence date | Measurement conditions | Provenance |
|---|---|---|---|---|---|---|---|
| arena_webdev | webdev / overall, latest split, revision 1880dbebff5b | 1632.3 | Arena score (Elo scale) | Unavailable | 2026-09-23 |
| Source |
Missing facts for Grok 4.7
model.hardware_fit_indeterminate: unknownmodel.languages: unknownmodel.max_output_tokens: not_disclosedmodel.parameters_total: unknownorigin.base_lineage: not_disclosedorigin.weights_hosting: not_disclosedoffering.api_model_id: unknownoffering.attestation.baa: requires_contractoffering.private_deployment: unknownoffering.router_slug: unknownoffering.speed.throughput: unknownoffering.speed.time_to_first_token: unknown
What this template teaches
A 60/40 blend lets a large price gap overturn a small quality lead.
Decision dec_a6d258fd73f7d9848e50fa39 on public snapshot snap_05a963d2477ac2fb.
Read the full dated job answer.
The live board uses current data. This link applies the template to its full lineup.
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