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.

Gemini 3.8 Flash vs Qwen3.8 Max 0902 for High volume (balanced), as of 2026-09-23

Find a text model for many short assistant requests that weighs quality and cost equally.

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.

Qwen3.8 Max 0902 has a 39% chance of matching or beating Gemini 3.8 Flash 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.

Short requests at scale; quality and cost weighted equally.

Requirements

• model.class = text-generator: The workload needs generated text responses.

Preferences

• chat_preference: Prefer assistants whose responses people rate more highly.
• -offering.cost_per_task: At volume, cost carries as much weight as quality.

Evidence for Gemini 3.8 Flash

Missing facts for Gemini 3.8 Flash

• model.hardware_fit_indeterminate: unknown
• model.languages: unknown
• model.parameters_total: unknown
• origin.base_lineage: not_disclosed
• origin.weights_hosting: not_disclosed
• offering.api_model_id: unknown
• offering.attestation.baa: not_disclosed
• offering.attestation.soc2: not_disclosed
• offering.private_deployment: unknown
• offering.router_slug: unknown
• offering.speed.throughput: unknown
• offering.speed.time_to_first_token: unknown

Evidence for Qwen3.8 Max 0902

Missing facts for Qwen3.8 Max 0902

• model.hardware_fit_indeterminate: unknown
• model.languages: unknown
• model.parameters_total: unknown
• origin.base_lineage: not_disclosed
• origin.lab_jurisdiction: not_disclosed
• origin.weights_hosting: not_disclosed
• offering.api_model_id: unknown
• offering.attestation.baa: not_disclosed
• offering.attestation.soc2: not_disclosed
• offering.data.retention: not_disclosed
• offering.data.zero_retention: not_disclosed
• offering.price.batch_input: not_disclosed
• offering.price.batch_output: not_disclosed
• offering.price.cached_input: not_disclosed
• offering.private_deployment: unknown
• offering.router_slug: unknown
• offering.speed.throughput: unknown
• offering.speed.time_to_first_token: unknown

What this template teaches

An even split is the neutral starting point; move the weights once you know what a request is worth.

Decision dec_f9b0517832771d05dada0828 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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