Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

GPT-4o mini vs WizardLM-2 8x22B benchmark

Name: GPT-4o mini vs WizardLM-2 8x22B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares GPT-4o mini (OpenAI) and WizardLM-2 8x22B (Microsoft AI) using the latest snapshots we have as of Aug 17, 2026. GPT-4o mini wins on output price at $0.6/1M. GPT-4o mini has the larger context window (128k tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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OpenAI

GPT-4o mini

Legacy small OpenAI model. Useful as a cheap baseline.

4o MiniElo 1,272$0.6/1M out

Microsoft AI

WizardLM-2 8x22B

Auto-discovered from OpenRouter (microsoft/wizardlm-2-8x22b). Preview until a second source matches.

$0.62/1M out

Model Lineage & Multi-Tier Derivatives🇺🇸 US Frontier

GPT-4 Series Family (4 models)

Compare vs Base (GPT-4o)

GPT-4o

OpenAI

Flagship Base

Elo

1335

Speed

110 tok/s

Price

$10.00 / 1M

View model →vs this

GPT-4o mini

OpenAI

4o Mini

Elo

1272

Speed

160 tok/s

Price

$0.60 / 1M

-63 Elo-94% cost1.5x speed

Viewing now

GPT-4.5 Orion

OpenAI

Derivative

Elo

1540

Speed

60 tok/s

Price

$150.00 / 1M

+205 Elo+1400% cost0.5x speed

View model →vs this

OpenAI: GPT-4

OpenAI

Derivative

Elo

—

Speed

—

Price

$60.00 / 1M

+500% cost

View model →vs this

Swap or Add Any Model to this Matchup

Instant pairwise benchmark recalculation across 400+ LLMs

Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-4o mini (9)vsWizardLM-2 8x22B (0)

GPT-4o mini: 9W (100%)Overall: GPT-4o miniWizardLM-2 8x22B: 0W (0%)

← GPT-4o miniWizardLM-2 8x22B →

GPT-4o mini (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,272vs—

Coding Elo

—vs—

SWE-bench

41.2%vs—

LiveBench

48.1%vs—

GPQA Diamond

60.1%vs—

GPT-4o mini: 4WWizardLM-2 8x22B: 0W

GPT-4o mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

160 tok/svs—

Time to first token

130 msvs—

GPT-4o mini: 2WWizardLM-2 8x22B: 0W

GPT-4o mini (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.6/1Mvs$0.62/1M

Input price

$0.15/1Mvs$0.62/1M

Context window

128kvs66k

GPT-4o mini: 3WWizardLM-2 8x22B: 0W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageGPT-4o mini 6/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

GPT-4o mini

$0.02/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,272

EloHigh is better

—

LiveBench

High is better

48.1%

LiveBenchHigh is better

—

SWE-bench

High is better

41.2%

SWE-benchHigh is better

—

GPQA

High is better

60.1%

GPQAHigh is better

—

TTFT

Low is better

130 ms

TTFTLow is better

—

Speed

High is better

160 tok/s

SpeedHigh is better

—

In $

Low is better

+313%$0.15 / 1M

In $Low is better

$0.62 / 1M

Out $

Low is better

+3%$0.60 / 1M

Out $Low is better

$0.62 / 1M

Context

High is better

+95%128k

ContextHigh is better

66k

Interactive Simulator (USD)

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save up to 54% with GPT-4o mini

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

GPT-4o mini$14.25 / mo

In: $5.25Out: $9

WizardLM-2 8x22B$31.00 / mo

In: $21.7Out: $9.3

Estimated Cost Delta

GPT-4o mini is estimated to save $16.75/month ($201/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
GPT-4o mini:Pick GPT-4o mini when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGPT-4o mini

Lower output list price ($0.6/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGPT-4o mini

Larger window (128k).

Screenshots / visionGPT-4o mini

GPT-4o mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	GPT-4o mini	Lower output list price ($0.6/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	GPT-4o mini	Larger window (128k).
Screenshots / vision	GPT-4o mini	GPT-4o mini is the side marked multimodal in the catalog.

Community Sentiment

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CompareLLM Matrix

Verified head-to-head card

LIVE

OpenAI

GPT-4o mini

Elo 1,272

LiveBench48.1%

SWE-bench41.2%

Speed160 tok/s

Output cost$0.6/1M

Microsoft AI

WizardLM-2 8x22B

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0.62/1M

Frequently Asked Questions

Which is better overall, GPT-4o mini or WizardLM-2 8x22B?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, GPT-4o mini or WizardLM-2 8x22B?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: GPT-4o mini output tokens are $0.6/1M versus $0.62/1M. Input prices and retry rates still move the real bill.
Which is faster, GPT-4o mini or WizardLM-2 8x22B?: We do not have TTFT for both models.
Which has the larger context window?: GPT-4o mini accepts 128k tokens versus 66k.
Can I self-host either model?: Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. GPT-4o mini and WizardLM-2 8x22B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All GPT-4o mini matchups →|All WizardLM-2 8x22B matchups →

GPT-4o mini vs OpenAI o1-mini (next gpt-mini)GPT-5 vs GPT-4o mini GPT-4.5 Orion vs GPT-4o mini GPT-5.6 Sol vs GPT-4o mini GPT-5.6 Terra vs GPT-4o mini GPT-4 Turbo vs GPT-4o mini

GPT-4o mini vs WizardLM-2 8x22B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

GPT-4o mini (9)vsWizardLM-2 8x22B (0)

GPT-4o mini: 9W (100%)Overall: GPT-4o miniWizardLM-2 8x22B: 0W (0%)

← GPT-4o miniWizardLM-2 8x22B →

GPT-4o mini (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,272vs—

Coding Elo

—vs—

SWE-bench

41.2%vs—

LiveBench

48.1%vs—

GPQA Diamond

60.1%vs—

GPT-4o mini: 4WWizardLM-2 8x22B: 0W

GPT-4o mini (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

160 tok/svs—

Time to first token

130 msvs—

GPT-4o mini: 2WWizardLM-2 8x22B: 0W

GPT-4o mini (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.6/1Mvs$0.62/1M

Input price

$0.15/1Mvs$0.62/1M

Context window

128kvs66k

GPT-4o mini: 3WWizardLM-2 8x22B: 0W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGPT-4o mini

Lower output list price ($0.6/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGPT-4o mini

Larger window (128k).

Screenshots / visionGPT-4o mini

GPT-4o mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	GPT-4o mini	Lower output list price ($0.6/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	GPT-4o mini	Larger window (128k).
Screenshots / vision	GPT-4o mini	GPT-4o mini is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, GPT-4o mini or WizardLM-2 8x22B?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, GPT-4o mini or WizardLM-2 8x22B?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

GPT-4o mini output tokens are $0.6/1M versus $0.62/1M. Input prices and retry rates still move the real bill.

Which is faster, GPT-4o mini or WizardLM-2 8x22B?

We do not have TTFT for both models.

Which has the larger context window?

GPT-4o mini accepts 128k tokens versus 66k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. GPT-4o mini and WizardLM-2 8x22B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.