Claude Fable 5$22.000/MClaude Opus 4.8$11.000/MClaude Opus 4.7$11.000/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-5.5$12.500/MGPT-5.2$5.425/MGPT-5.2-Codex$5.425/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 3.5 Pro$5.000/MGemini 3.1 Pro$5.000/MGemini 3 Pro$5.000/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/MClaude Fable 5$22.000/MClaude Opus 4.8$11.000/MClaude Opus 4.7$11.000/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-5.5$12.500/MGPT-5.2$5.425/MGPT-5.2-Codex$5.425/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 3.5 Pro$5.000/MGemini 3.1 Pro$5.000/MGemini 3 Pro$5.000/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/M
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WizardLM-2 8x22B (DI)

Fine-tuned

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 (DI) is a frontier AI model from DeepInfra. It costs $0.630 per million input tokens and $0.630 per million output tokens (blended $0.630/M), with a 64K-token context window.

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 ↗Provider pricing ↗API docs ↗Compare with another model →Estimate monthly cost →
INPUT
$0.630/M
per million input tokens
OUTPUT
$0.630/M
per million output tokens
BLENDED 70/30
$0.630/M
default reference rate · how it's calculated →
CONTEXT
64K
64,000 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.
More from DeepInfra
See all 11 →
Llama 3.3 70B (DI)
Serverless · 128K ctx
in $0.230/Mout $0.400/M
Llama 3.1 405B (DI)
Serverless · 128K ctx
in $0.800/Mout $0.800/M
Llama 3.1 70B (DI)
Balanced · 128K ctx
in $0.350/Mout $0.400/M
Mistral 7B (DI)
Nano · 32K ctx
in $0.070/Mout $0.070/M
Mixtral 8x7B (DI)
MoE · 32K ctx
in $0.240/Mout $0.240/M
DeepSeek-R1 (DI)
Reasoning · 64K ctx
in $0.550/Mout $2.190/M
Frequently asked questions

How much does WizardLM-2 8x22B (DI) cost?

WizardLM-2 8x22B (DI) costs $0.630 per million input tokens and $0.630 per million output tokens, for a blended reference rate of $0.630 per million tokens.

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

WizardLM-2 8x22B (DI) supports up to 64K tokens of context (64,000 tokens).

What is WizardLM-2 8x22B (DI) best for?

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

Who makes WizardLM-2 8x22B (DI)?

WizardLM-2 8x22B (DI) is developed and served by DeepInfra. It was released in Apr 2024.