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Model profile
Unknown

Cogito v2.1 (Reasoning)

Cogito v2.1 (Reasoning) is a budget text-first model from Unknown with a fast runtime profile, unknown context posture, and the clearest fit around reasoning / long-context research.

Best for: Reasoning / Long-context researchFast latencyUnknown contextBudget pricing
Intelligence
N/A

Benchmark blend

Coding
24.8

Dev workflow signal

Context
N/A

Unknown

Input Price
$1.25

Budget tier

Decision snapshot
53

Cogito v2.1 (Reasoning) currently reads as a budget text-first option with unknown context and a fast runtime profile.

Overall profile
Use-case specific
Best for
Reasoning / Long-context research
Latency tier
Fast
Price tier
Budget
Source coverage
OpenRouterArtificial Analysis
Compare this modelSee leaderboard

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
N/A
44

General reasoning and benchmark headroom.

Situational
Speed
99 tok/s
85

TTFT 0.39s

Above average
Context
N/A
34

How much prompt and task state can stay in view.

Limited
Price
$1.25
86

$1.25 output / 1M

Efficient

Editorial Profile

Cogito v2.1 (Reasoning) in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Use-case specificCoding score 25Math score 73

The Cogito v2.1 (Reasoning) AI model by Unknown.

Identity

Unknown text-first profile

Positioning

Reasoning / Long-context research with unknown context and fast runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths

  • Latency and throughput look responsive enough for interactive loops.

Tradeoffs

  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

Best fit

  • Focused chat, retrieval-augmented flows, and narrower production tasks.

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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

MMLU Pro
84.9%
GPQA
76.8%
HLE
11.0%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
24.8
LiveCodeBench
0.688
SciCode
41.0%
Math

Formal reasoning, structured problem solving, and competition-style math.

Math Index
72.7
AIME 2025
72.7%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
46.3%
TerminalBench Hard
16.7%
LCR
21.7%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
N/A
Vision
Text-first
Price architecture
Input
per 1M input tokens
$1.25
Output
per 1M output tokens
$1.25
Blended
AA 3:1 mix
$1.25

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.