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WizardLM-2 8x22B

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Largest open-weights Mixtral MoE. Cheap-to-serve frontier-ish quality before Llama 3.1 405B and DeepSeek V3 took the open-weights lead.

WizardLM-2 8x22B is a efficient AI model from Microsoft. It costs $0.620 per million input tokens and $0.620 per million output tokens (blended $0.620/M), with a 65,535-token context window.

Profile inherited from upstream Mixtral 8x22B (WizardLM-2 base) ↗ — this is a hosted variant of the same open-weights model.

INPUT
$0.620/M
per million input tokens
OUTPUT
$0.620/M
per million output tokens
BLENDED 70/30
$0.620/M
unchanged since 3 May
CONTEXT
65,535
tokens
What it is good at
  • Open-weights MoE
  • Cheap inference per active parameter
  • 64K context
Typical use cases
  • Self-hosted chat at scale
  • Fine-tune base

Benchmarks

vs. best public score
Scores inherited from Mixtral 8x22B (WizardLM-2 base) — this is a hosted variant of the same open-weights model, so the underlying benchmark scores are identical.
MMLU78%
Multitask academic knowledge across 57 subjects.
Graduate-level science questions, "Google-proof".
MATH42%
High-school competition math problems.
Python function synthesis from docstrings.
LMArena Elo1198 Elo
Crowd-sourced head-to-head preference Elo rating.
Hand-curated from each provider's published reports and public leaderboards. Methodology varies across sources, treat as directional rather than authoritative.

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Frequently asked questions

How much does WizardLM-2 8x22B cost?

WizardLM-2 8x22B costs $0.620 per million input tokens and $0.620 per million output tokens, for a blended reference rate of $0.620 per million tokens.

What is WizardLM-2 8x22B's context window?

WizardLM-2 8x22B supports up to 65,535 tokens of context in a single request.

What is WizardLM-2 8x22B best for?

WizardLM-2 8x22B is well suited to Open-weights MoE, Cheap inference per active parameter and 64K context.

Who makes WizardLM-2 8x22B?

WizardLM-2 8x22B is developed and served by Microsoft. It was released in Apr 2024.

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