Claude Opus 4.6$11.000/MClaude Opus 4.5$33.000/MClaude Sonnet 3.7$6.600/MClaude Opus 3$33.000/MClaude 2.1$12.800/MClaude 2$12.800/MGPT-5$3.875/MGPT-4.5$97.500/MGPT-4 Turbo Preview$16.000/MGPT-4$39.000/MGPT-4-32k$78.000/Mo3$19.000/Mo3-mini$2.090/Mo4-mini$2.090/Mo1$28.500/Mo1-mini$5.700/Mo1-preview$28.500/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/MPaLM 2 Bison$0.500/MPaLM 2 Unicorn$5.000/MGemma 3 27B$0.270/MGrok 3$6.600/MGrok 2$4.400/MGrok 1.5$8.000/MDeepSeek-V3$0.519/MDeepSeek-V3-0324$0.519/MDeepSeek-R1$1.042/MClaude Opus 4.6$11.000/MClaude Opus 4.5$33.000/MClaude Sonnet 3.7$6.600/MClaude Opus 3$33.000/MClaude 2.1$12.800/MClaude 2$12.800/MGPT-5$3.875/MGPT-4.5$97.500/MGPT-4 Turbo Preview$16.000/MGPT-4$39.000/MGPT-4-32k$78.000/Mo3$19.000/Mo3-mini$2.090/Mo4-mini$2.090/Mo1$28.500/Mo1-mini$5.700/Mo1-preview$28.500/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/MPaLM 2 Bison$0.500/MPaLM 2 Unicorn$5.000/MGemma 3 27B$0.270/MGrok 3$6.600/MGrok 2$4.400/MGrok 1.5$8.000/MDeepSeek-V3$0.519/MDeepSeek-V3-0324$0.519/MDeepSeek-R1$1.042/M

MicrosoftEfficientLIVE INDEX

WizardLM-2 8x22B

Name: WizardLM-2 8x22B
Brand: Microsoft
Price: 0.620000 USD

text->text

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

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

Released Apr 2024Modalities textOfficial model page ↗API docs ↗Pricing source ↗Compare with another model →Estimate monthly cost →

INPUT

$0.620/M

per million input tokens

OUTPUT

$0.620/M

per million output tokens

BLENDED 70/30

$0.620/M

default reference rate

CONTEXT

66K

65,535 tokens

What it's 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.

GPQA Diamond36%

Graduate-level science questions, "Google-proof".

MATH42%

High-school competition math problems.

HumanEval76%

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.