ReMM SLERP 13B APIOPEN WEIGHTS6K context

Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).

What is ReMM SLERP 13B?

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

ReMM SLERP 13B pricing

Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):

On output price, ReMM SLERP 13B is cheaper than 70% of the 309 models in the catalog. It is served by 2 providers; the best combined rate at our last snapshot was ≈ $0.45 / $0.65 per 1M via NextBit, with upstream quantizations bf16, fp8.

What ReMM SLERP 13B costs per month

Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.

ReMM SLERP 13B vs alternatives

When not to use ReMM SLERP 13B

• Its 6K context is small — not ideal for large documents or big codebases.

Specs

How to call ReMM SLERP 13B

Copyfrom openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
    model="undi95/remm-slerp-l2-13b",
    messages=[{"role": "user", "content": "Hello"}],
)
print(resp.choices[0].message.content)

Copycurl https://api.datallmlab.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"undi95/remm-slerp-l2-13b","messages":[{"role":"user","content":"Hello"}]}'

Copyimport OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
  model: "undi95/remm-slerp-l2-13b",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes ReMM SLERP 13B and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for ReMM SLERP 13B

• Be explicit and show the shape of the answer. Spell out format, tone and constraints up front, and include one short example of the output you want — ReMM SLERP 13B follows concrete instructions better than abstract ones.
• Constrain JSON with a schema. Use response_format / structured outputs rather than "reply in JSON" to get valid, parseable objects every time.
• Cheap enough to batch. Great for high-volume classification, extraction and drafting — template the prompt, batch requests, and validate outputs programmatically.

Tips are derived from ReMM SLERP 13B's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for ReMM SLERP 13B

Popular open-source projects for running and building with ReMM SLERP 13B — star counts pulled from GitHub (July 2026).

Listed by GitHub stars; inclusion is by ecosystem relevance (inference engines, agent frameworks and SDKs), not affiliation. Stars change — see each repo for current numbers.

Migrating to ReMM SLERP 13B

Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → undi95/remm-slerp-l2-13b. Messages, streaming and the rest of your code stay the same. Routing & failover guide.

Self-host or use the API?

ReMM SLERP 13B ships open weights (Undi95/ReMM-SLERP-L2-13B, ~426 downloads and 27 likes in the last 30 days), with community quantizations (bf16, fp8) for smaller GPUs, so you can run it yourself. Most teams still use the API: no GPU to provision or keep warm, no inference ops, and instant access across 2 providers with automatic failover. Self-host when data residency or fixed per-token economics matter most.

Rate limits & reliability

Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff; because ReMM SLERP 13B is served by 2 providers, requests can fail over to a healthy one automatically. See the error-code guide and failover setup.

Related reading

Frequently asked questions