Jamba-Instruct
Jamba-Instruct is worth evaluating for long context when its provider route and context window match the workload.
Use it for
- Teams evaluating long context
- Workloads that can use a 256k context window
- Buyers comparing 2 tracked provider routes
Do not use it for
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- Jamba
- Released
- 2024-05-02
- Context
- 256k
- Parameters
- 52B (12B active)
- Architecture
- Mixture of Experts
- Knowledge cutoff
- 2024-03
- Specialization
- general
- Openness
- Open source
- License
- Apache 2.0OSI-approvedCommercial use: permitted
- Weights
- Unknown
- Code
- Unknown
- Training
- Fine-tuned
Cheapest of 2 routes · AI21 Studio
About
Jamba-Instruct, developed by AI21 Labs, is a cutting-edge large language model tailored for enterprise applications. It boasts a remarkable 256,000-token context window, enabling it to process vast amounts of data, equivalent to an 800-page novel, making it ideal for tasks like summarization, question answering, and document analysis. Utilizing a hybrid architecture that blends Structured State Space (SSM) technology with traditional Transformer layers, Jamba-Instruct is designed for optimal performance and efficiency in managing long-context scenarios. Instruction-tuned to handle complex commands and engage in open-ended dialogues, it prioritizes high safety standards, making it suitable for diverse applications such as chatbots, financial analysis, and legal document summaries while maintaining cost-effectiveness and low latency 2512.
Jamba-Instruct is an open-source model in the Jamba family. The structured metadata tracks a 256k-token context window. This page tracks provider routes through AI21 Studio and Microsoft Foundry, with the cheapest tracked route listed at $0.5 input and $0.7 output per 1M tokens. No headline benchmark score is tracked for Jamba-Instruct yet.
Top use-case fit
Long context
Included by capability and metadata signals in the decision map.
Provider price ladder
Compare all 2Compare API pricing across 2 providers for input and output tokens, batch, and cached reads when available.
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| AI21 Studio | $0.500 | $0.700 | Serverless |
| Microsoft Foundry | $0.500 | $0.700 | Serverless |
Available via routers & gateways(5)
LiteLLM
GatewayOpen-source Python SDK and proxy server that unifies 100+ LLM APIs behind a single OpenAI-compatible interface, with load balancing, cost tracking, and configurable failover.
Portkey
GatewayProduction AI gateway routing to 1,600+ LLMs with failover, load balancing, semantic caching, and guardrails; Apache 2.0 core is fully self-hostable with the complete feature set.
Azure AI Foundry Model Router
RouterMicrosoft Azure AI Foundry's native model router that uses a trained ML model to route each prompt in real time to the optimal Azure-hosted model, with Balanced/Cost/Quality mode selection and automatic failover.
Helicone
GatewayObservability-first AI gateway with routing, caching, rate limiting, and request tracing; Apache 2.0 open-source core with a managed hosted tier for logging and analytics.
Kong AI Gateway
GatewayMulti-LLM AI gateway built on Kong Gateway 3.x, adding semantic routing, load balancing, guardrails, and MCP traffic analytics as plugins over Kong's existing API management platform.
Capabilities
No model capability flags are currently sourced.
Benchmark peer barsfor Long context
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
Frequently asked questions
What is the context window of Jamba-Instruct?
Jamba-Instruct has a context window of 256k tokens.
How much does Jamba-Instruct cost?
Jamba-Instruct pricing ranges from $0.50/1M to $0.5/1M input tokens depending on the provider.
When was Jamba-Instruct released?
Jamba-Instruct was released on 2024-05-02.
Which providers offer Jamba-Instruct?
Jamba-Instruct is available from 2 providers: AI21 Studio, Microsoft Foundry.
Cheapest of 2 routes · AI21 Studio