Capability
55.4/100
field median 58.1
#100 of 232 ranked models
Trinity-Large-Preview
Released Jan 27, 2026 — see all recent releases
Decision reading
Trinity-Large-Preview scores 55.4 out of 100 and ranks #100 of 232. This profile shows 4 source-displayable benchmark rows. API pricing is $0.25 input and $1 output per million tokens.
Data as of September 4, 2026 · How the score is built
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Strongest published evidence
Published rows are visible, but no category has enough eligible evidence for a comparative rank.
Validate before choosing
4 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Price
$0.25input / $1 output
input median $1
blended $0.63
Speed
Not measured
field median 92 tok/s
Time to first token not measured
Context
512Ktokens
field median 256,000
Reported for this model; direct source link not stored
What it costs to get this score
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Current modelTrinity-Large-Preview · 55.4 score · $0.63 blended per million tokens
Horizontal: blended price per million tokens, log scale · Vertical: public score
How 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.
- AgenticNot measured
- CodingNot measured
- ReasoningNot measured
- Knowledge3/3 verified
- Math1/1 verified
- MultilingualNot measured
- MultimodalNot measured
- Inst. FollowingNot measured
Verified sourceProvisionalNot measured
Spec 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
- Not published
- Context window
- 512K
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- Not sourced yet
- Cloud regions
- Not tracked yet
- Lifecycle
- Established
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing record
- Self-host
- Open weights available; hardware estimate not sourced
- Rate limits
- Not tracked yet
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.
Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.
Estimate VRAM from known parametersCategory 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%0 benchmarksNot measured | Not measured | Not ranked | Not available | 22% | 0 benchmarks | Not measured |
| CodingWeight 20%0 benchmarksNot measured | Not measured | Not ranked | Not available | 20% | 0 benchmarks | Not measured |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeRank Not rankedWeight 12%3 benchmarksVerified | 22.5 | Not ranked | Not available | 12% | 3 benchmarks | Verified |
| MathWeight 5%1 benchmarkVerified | Score pending | Not ranked | Not available | 5% | 1 benchmark | Verified |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
Benchmark ledger
Knowledge opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Knowledge3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMLUMassive Multitask Language Understanding | Score87.2% | Versus best verified row Best verified: o1 · 91.8% | Gap4.6 behind | WeightDisplay only | Provider exact |
| MMLU-Pro (Arcee)MMLU-Pro first-party comparison snapshot | Score75.2% | Versus best verified row Best verified: Trinity-Large-Preview · 75.2% | GapBest verified | WeightDisplay only | Provider exact |
| GPQA-DGPQA Diamond | Score63.3% | Versus best verified row Best verified: GPT-6 Astra · 96.0% | Gap32.7 behind | WeightDisplay only | Provider exact |
Math1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| AIME25 (Arcee)AIME25 first-party comparison snapshot | Score24.0% | Versus best verified row Best verified: Trinity-Large-Preview · 24.0% | GapBest verified | WeightDisplay only | Provider exact |
Lineage
The sequence follows explicit supersedes links. A successor's displayed score stays at least 0.1 points above its predecessor; raw benchmark rows do not move. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Jan 27, 2026 · you are here
Trinity-Large-PreviewScore 55.4 · $0.25 / $1
preview · preview
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.
Trinity-Large-Preview ranks #100 of 232 on the public leaderboard with a score of 55.39/100. It does not yet have enough sourced coverage for a verified position.
Trinity-Large-Preview is a open weight model with a 512K context window. No explicit reasoning mode is documented in this profile.
Official exact-value snapshot from Arcee AI's January 27, 2026 Trinity Large launch post and model docs. BenchLM stores the published preview values as a sparse, non-ranked row because benchmark coverage is too limited for weighted leaderboard inclusion.
Trinity-Large-Preview sits in the Trinity Large family with Trinity-Large-Thinking. 4 of 422 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Radar
Full release historyTrinity-Large-Preview release history
Trinity-Large-Preview released
Arcee AI · Model release
Source confirmed
Radar confirmed these at the source. Already tracking Trinity-Large-Preview? See the free Radar Brief for what changes next.
Frequently asked questions
How does Trinity-Large-Preview perform overall in AI benchmarks?
Trinity-Large-Preview ranks #100 out of 232 models on the public BenchAlign leaderboard, with a score of 55.39/100. Its evidence status is Estimated, and this profile shows 4 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Trinity-Large-Preview good for knowledge and understanding?
Trinity-Large-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 Trinity-Large-Preview good for mathematics?
Trinity-Large-Preview has source-displayable benchmark coverage for mathematics, 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 Trinity-Large-Preview open source?
Trinity-Large-Preview is an open-weight model from Arcee AI. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Which sibling models are related to Trinity-Large-Preview?
Trinity-Large-Preview belongs to the Trinity Large family. Related tracked variants include Trinity-Large-Thinking. 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 Trinity-Large-Preview have full benchmark coverage on BenchLM?
No. Trinity-Large-Preview currently has 20 source-displayable rows across 422 tracked benchmark slots. 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 Trinity-Large-Preview?
Trinity-Large-Preview has a reported context window of 512K in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.
Compare Trinity-Large-Preview with every tracked model410 comparisons
Last updated September 4, 2026. Runtime fields remain blank until a sourced snapshot exists.
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