Data as of November 13, 2026 · How the score is built
Pareto 26.10 Preview
Decision readingPareto 26.10 Preview is tracked, but not publicly ranked yet. The profile exposes 3 sourced benchmark rows and leaves unsupported fields blank until a published record exists.
Email me when its price, rank or availability changes.
Capability
Unranked
field median 49.4Not eligible for a public rank
Price
$2.50input / $7.50 output
input median $0.60cached $0.25 · blended $5
Speed
Not measured
field median 92 tok/sTime to first token not measured
Context
Not published
field median 256,000No exact-model context limit is sourced
Decision snapshot
How much published evidence this model has, where that evidence is strongest, and what to validate before choosing it. It has no public rank, so no field position is shown.
Strongest published evidence
Published rows are visible, but no category has enough eligible evidence for a comparative rank.
Validate before choosing
3 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.
Source-linked · 3 displayable benchmark rows
Category score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticWeight 22%1 benchmarkVerified | Score pending | 1 benchmark | Verified | |||
| CodingWeight 20%1 benchmarkVerified | Score pending | 1 benchmark | Verified | |||
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeWeight 12%1 benchmarkVerified | Score pending | 1 benchmark | Verified | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured |
3 of 919 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic1/1 verified
- Coding1/1 verified
- ReasoningNot measured
- MultimodalNot measured
- Knowledge1/1 verified
- MultilingualNot measured
- Inst. FollowingNot measured
- MathNot measured
Benchmark ledger
Every result says who ran the test. For this model, Unbiased ran all 3. Coding opens by default. The tick marks the best source-verified result in the catalog; provisional leaders do not set the reference.
Coding1 row
| Benchmark | Score | Versus best verified row | Gap | Who ran it | Use in ranking |
|---|---|---|---|---|---|
| DeepSWE | 69.9% | Best verified: Muse Wonder Full · 79.0% | Gap9.1 behind | Reported by Unbiased | Shown only |
Agentic1 row
| Benchmark | Score | Versus best verified row | Gap | Who ran it | Use in ranking |
|---|---|---|---|---|---|
| Terminal-Bench 4.0 | 50.80% | Best verified: Claude Sonnet 5.5 · 70.60% | Gap19.8 behind | Reported by Unbiased | Shown only |
Knowledge1 row
| Benchmark | Score | Versus best verified row | Gap | Who ran it | Use in ranking |
|---|---|---|---|---|---|
| GPQA-DGPQA Diamond | 92.4% | Best verified: GPT-6 Astra · 96.0% | Gap3.6 behind | Reported by Unbiased | Shown only |
Outlined bars are lab-reported. Filled bars are benchmark-run or independent. Bars run 0–100; the dark tick marks the best source-verified value.
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Base entry
Pareto 26.9Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- paretoUnbiased API documentation
- Context window
- Not publishedUnbiased Pareto 26.10 Preview model card
- Maximum output
- Not sourced yetUnbiased API documentation
- Knowledge cutoff
- Not sourced yet
- Input modalities
- text, imageOpenRouter Pareto 26.10 Preview route
- Output modalities
- textOpenRouter Pareto 26.10 Preview route
- Parameters
- Not disclosed by the provider
- Availability
- Unbiased Chat Completions API · Unbiased Messages API · OpenRouterUnbiased API documentation
OpenRouter: unbiased/pareto-26.10-preview supports tools, a 1,048,576-token context, and up to 131,072 output tokens. These limits apply to that route; Unbiased does not publish direct-API limits. The direct pareto alias serves the current release. OpenRouter Pareto 26.10 Preview route, read Oct 1, 2026
- Cloud regions
- Not tracked yet
- Lifecycle
- previewUnbiased product updates
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Published at $0.25 per million cached input tokensUnbiased direct API pricing
- Self-host
- Weights are not published
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
We track Pareto 26.10 Preview, but the public leaderboard excludes this profile until enough non-generated benchmark coverage is available. Only published rows appear above.
Pareto 26.10 Preview is a proprietary model. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Available through Unbiased’s OpenAI-compatible and Anthropic-compatible API at https://api.unbiased.ai/v1 using the mutable model string `pareto`, with manually approved access. OpenRouter lists the separate route `unbiased/pareto-26.10-preview` with text and image input, text output, tools, a 1,048,576-token context, and up to 131,072 output tokens. Those limits describe the OpenRouter route; Unbiased does not publish a direct-API context or output limit. No weights are published.
Pareto blends several models on each request and returns one answer. Its composition can change between releases, so these results describe the 26.10 Preview product configuration. We keep all results outside the overall and category rankings. Unbiased reports preliminary October 1, 2026 results of 69.9 on DeepSWE v1.1, 50.8 on Terminal-Bench 4.0, and 92.4 on GPQA-Diamond; denominators and evaluation settings remain unconfirmed. The reported HLE text-only score of 49.9 is not stored as a benchmark row because the run’s tool setting is unspecified. We preserve Pareto 26.9’s historical results separately and do not import the competitor scores or convert task costs into token prices.
Pareto 26.10 Preview sits in the Pareto family with Pareto 26.9. Its explicit predecessor is Pareto 26.9. 3 of 919 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Last updated November 13, 2026. Runtime fields remain blank until a sourced snapshot exists.
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Where to run Pareto 26.10 Preview by API
OpenRouter is the one host we track that publishes a per-token price for it. Prices read from each host’s own pages on November 11, 2026.
| Host | Input /1M | Output /1M | Cached /1M | Context |
|---|---|---|---|---|
| OpenRouterServes Pareto 26.10 | $0.80 | $3.20 | $0.03 | 1.05M |
Questions
How does Pareto 26.10 Preview perform overall in AI benchmarks?
Pareto 26.10 Preview has 3 source-displayable benchmark rows, but it does not qualify for a public overall rank. The available rows remain visible by category without being converted into a site-wide score. Missing evidence stays blank instead of being estimated from an earlier model.
Is Pareto 26.10 Preview good for knowledge and understanding?
Pareto 26.10 Preview has source-displayable benchmark coverage for knowledge and understanding, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Pareto 26.10 Preview good for coding and programming?
Pareto 26.10 Preview has source-displayable benchmark coverage for coding and programming, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Pareto 26.10 Preview good for agentic tool use and computer tasks?
Pareto 26.10 Preview has source-displayable benchmark coverage for agentic tool use and computer tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Which sibling models are related to Pareto 26.10 Preview?
Pareto 26.10 Preview belongs to the Pareto family. Related tracked variants include Pareto 26.9. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does Pareto 26.10 Preview have full benchmark coverage on BenchLM?
No. Pareto 26.10 Preview currently has 3 source-displayable rows. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of Pareto 26.10 Preview?
Pareto 26.10 Preview's provider has not published a context-window limit for this exact model. The profile leaves the value unavailable instead of borrowing a number from an earlier family member or a third-party route. Maximum output length is tracked separately when the provider documents it.