01 / Efficiency
100B scale aimed at intelligence efficiency
Elephant Alpha is positioned as a dense, capable text model rather than an oversized general-purpose stack, which makes it easier to reason about in focused product flows.
Independent Model Guide
Elephant Alpha
Elephant Alpha is presented on OpenRouter as a 100B-parameter text model built for intelligence efficiency, code-heavy tasks, document work, and lightweight agents that need 256K context without a sprawling interface.
Independent editorial page. Data points reflect the public OpenRouter listing checked on April 19, 2026. This site is not affiliated with OpenRouter.
- Release
- Apr 13, 2026
- Scale
- 100B params
- Context
- 256K tokens
- Output
- 32K max
Core Traits
Function calling, structured output, prompt caching
Workflow Fit
Code completion, debugging, document parsing, compact agent loops
API Shape
OpenAI-compatible access through OpenRouter providers
Capabilities
Elephant Alpha focuses on long context and predictable output.
The model profile is most compelling when you need a long window, predictable outputs, and a fast path to integration instead of a feature zoo.
02 / Long Context
256K context for codebases, specs, and large documents
The listed context window is large enough for multi-file reasoning, policy packs, and document-heavy workflows that would otherwise need chunking gymnastics.
03 / Structured Work
Function calling and schema-shaped output
Structured output and tool invocation make the model more useful in systems that need reliable JSON, dispatcher steps, or deterministic hand-offs to downstream code.
Use Cases
Where Elephant Alpha fits best in real workflows.
This is a practical fit analysis, not a benchmark theater page. The common thread is long context plus disciplined output.
Code Completion
Use it when prompts need repository history, local conventions, and multi-file context in one pass.
Debugging
Useful for tracing log context, reproducing failures, and returning structured remediation steps.
Document Processing
Fits extraction, summarization, and schema-mapped parsing across long reports or knowledge bases.
Lightweight Agents
Function calling plus prompt caching gives it a cleaner path into compact agent loops and operator UIs.
API & Compatibility
Provider-ready traits without extra storytelling.
OpenRouter presents Elephant Alpha through an OpenAI-compatible surface. The operational questions are mostly about context, output shape, and provider routing.
Quick Read
- Model slug:
openrouter/elephant-alpha - Context window: 256K
- Max output: 32K
- Supports function calling
- Supports structured outputs
- Supports prompt caching
Operator Notes
- Best suited to long-context text workflows rather than image-heavy interfaces.
- Good candidate for tools that need predictable JSON or action plans.
- Verify provider logging and privacy settings before sending sensitive data.
- Use the source listing for current provider availability and pricing details.
Minimal Request Shape
{
"model": "openrouter/elephant-alpha",
"messages": [
{ "role": "system", "content": "Return JSON." },
{ "role": "user", "content": "Analyze this repository." }
]
}FAQ
Short answers to the questions that matter first.
What is Elephant Alpha?
Elephant Alpha is a 100B text model listed on OpenRouter. The public listing emphasizes intelligence efficiency, long context, and workflow-friendly output controls.
How much context and output does it support?
The current public listing shows a 256K context window and support for up to 32K output tokens.
What kinds of tasks is it strongest at?
The clearest fit is code completion, debugging, document processing, and lightweight agents that need structured output or tool calls.
Should I treat this page as the canonical source?
No. Use this page as a fast editorial brief, then click through to OpenRouter for the official model listing, provider availability, and pricing.
Next Step
Use this page as the front door, then validate on the source.
Elephant Alpha looks most interesting when your workflow is text-first, context-heavy, and sensitive to output shape. For provider routing and live pricing, go straight to the source listing.