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Model profile
undi95

ReMM SLERP 13B

ReMM SLERP 13B is a budget text-first model from undi95 with a heavy runtime profile, compact context posture, and the clearest fit around reasoning / coding.

Best for: Reasoning / CodingHeavy latencyCompact contextBudget pricing
Intelligence
N/A

Benchmark blend

Coding
N/A

Dev workflow signal

Context
6K Tokens

Compact

Input Price
$0.45

Budget tier

Decision snapshot
48

ReMM SLERP 13B currently reads as a budget text-first option with compact context and a heavy runtime profile.

Overall profile
Use-case specific
Best for
Reasoning / Coding
Latency tier
Heavy
Price tier
Budget
Source coverage
OpenRouter
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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
N/A
46

Latency data is partial.

Situational
Context
6K Tokens
28

How much prompt and task state can stay in view.

Limited
Price
$0.45
86

$0.65 output / 1M

Efficient

Editorial Profile

ReMM SLERP 13B 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 40Math score 36

A recreation trial of the original MythoMax-L2-B13 but with updated models. #merge

Identity

undi95 text-first profile

Positioning

Reasoning / Coding with compact context and heavy runtime.

Cost posture

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

Strengths

  • The available source data suggests a balanced profile rather than one dominant edge.

Tradeoffs

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

  • Latency profile is better for deliberate runs than rapid back-and-forth chat.

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

  • Context window is more comfortable for focused tasks than extremely long sessions.

Best fit

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

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.

No benchmark data is available for this model yet.

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
6K Tokens
Vision
Text-first
Modalities
text->text, text
Tokenizer
Llama2
Max Completion
4096
Moderation
No
Supported Parameters
frequency_penaltylogit_biaslogprobsmax_tokensmin_ppresence_penaltyrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetop_atop_ktop_logprobstop_p
Input Modalities
text
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.45
Output
per 1M output tokens
$0.65
Blended
AA 3:1 mix
N/A

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.