LLM Reference

Fireworks CodeLlama-34b-Instruct

Released
2023-07-18
Last refreshed
2026-05-19
Status
Researched 30d ago
Open weightsCommercial use: conditional

Fireworks CodeLlama-34b-Instruct is worth evaluating for general LLM work when its provider route and context window match the workload.

Use it for

  • Teams evaluating general LLM work
  • Workloads that can use a 16k context window
  • Buyers comparing 1 tracked provider route

Do not use it for

  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Released
2023-07-18
Context
16k
Parameters
34B
Architecture
Decoder Only
Knowledge cutoff
2024-03
Specialization
general
Openness
Open weights
License
Llama 2 CommunityCommercial use: conditional
Created by

Large-scale open-source AI for social technologies.

Menlo Park, California, United States
Founded 2013
Website
Pricing
Output / 1M
$0.300
Input / 1M
$0.300

Cheapest of 1 route · Fireworks AI

About

Fireworks CodeLlama-34b-Instruct is Meta's Code Llama model. It offers a 16K-token context window with weights openly available for self-hosting.

Fireworks CodeLlama-34b-Instruct is an open-weight model in the Code Llama family. The structured metadata tracks a 16k-token context window. This page tracks provider routes through Fireworks AI, with the cheapest tracked route listed at $0.3 input and $0.3 output per 1M tokens. No headline benchmark score is tracked for Fireworks CodeLlama-34b-Instruct yet.

Top use-case fit

No primary decision-task fit is mapped for this model yet.

Provider price ladder

Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
Fireworks AI$0.300$0.300
Serverless

Available via routers & gateways(1)

Capabilities

No model capability flags are currently sourced.

Benchmark peer barsfor Coding

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.