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Every score has a dated snapshot.

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  3. OpenAI: GPT-5 Image vs Llama 3.1 405B

Pairwise benchmark snapshot · Aug 16, 2026noindex (thin pair)

OpenAI: GPT-5 Image vs Llama 3.1 405B benchmark

This page compares OpenAI: GPT-5 Image (OpenAI) and Llama 3.1 405B (Meta) using the latest snapshots we have as of Aug 16, 2026. Llama 3.1 405B wins on output price at $3.5/1M. OpenAI: GPT-5 Image has the larger context window (400k 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.

Quick answer

OpenAI: GPT-5 Image vs Llama 3.1 405B is a dated snapshot, not a lab score. Llama 3.1 405B is the cheaper output token. Elo is crowd preference, not an exam. Pick the column that matches the job.
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OpenAI

OpenAI: GPT-5 Image

Auto-discovered from OpenRouter (openai/gpt-5-image). Preview until a second source matches.

$10/1M out

Meta

Llama 3.1 405B

Meta flagship open-weight 405B dense foundation model with 128k context window.

Elo 1,370$3.5/1M out

Swap or Add Any Model to this Matchup

Instant pairwise benchmark recalculation across 400+ LLMs

Model A
Model B
Quick vs:vs Claude Opus 4.5vs Claude Opus 4.6vs Claude Sonnet 4.5vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

OpenAI: GPT-5 Image (1)vsLlama 3.1 405B (9)
OpenAI: GPT-5 Image: 1W (10%)Overall: Llama 3.1 405BLlama 3.1 405B: 9W (90%)
← OpenAI: GPT-5 ImageLlama 3.1 405B →
Llama 3.1 405B (5/5)

Intelligence & Reasoning

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

Preference Elo
—vs1,370
Coding Elo
—vs1,385
SWE-bench
—vs58.4%
LiveBench
—vs61.2%
GPQA Diamond
—vs75.2%
OpenAI: GPT-5 Image: 0WLlama 3.1 405B: 5W
Llama 3.1 405B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed
—vs42 tok/s
Time to first token
—vs360 ms
OpenAI: GPT-5 Image: 0WLlama 3.1 405B: 2W
Llama 3.1 405B (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price
$10/1Mvs$3.5/1M
Input price
$10/1Mvs$1.25/1M
Context window
400kvs128k
OpenAI: GPT-5 Image: 1WLlama 3.1 405B: 2W
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 AdvantageLlama 3.1 405B 5/6
Preference Elo

No shared data

No shared data

Throughput Speed

No shared data

No shared data

Price Efficiency

Llama 3.1 405B

$6.50/1M cheaper

Full Benchmark Score Matrix

—
Elo
High is better
—
EloHigh is better
1,370
Code Elo
High is better
—
Code EloHigh is better
1,385
LiveBench
High is better
—
LiveBenchHigh is better
61.2%
SWE-bench
High is better
—
SWE-benchHigh is better
58.4%
GPQA
High is better
—
GPQAHigh is better
75.2%
TTFT
Low is better
—
TTFTLow is better
360 ms
Speed
High is better
—
SpeedHigh is better
42 tok/s
In $
Low is better
$10/1M
In $Low is better
$1.25/1M+700%
Out $
Low is better
$10/1M
Out $Low is better
$3.5/1M+186%
Context
High is better
+213%400k
ContextHigh is better
128k
Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Save up to 81% with Llama 3.1 405B
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
OpenAI: GPT-5 Image$500.00 / mo
In: $350.00Out: $150.00
Llama 3.1 405B$96.25 / mo
In: $43.75Out: $52.50
Estimated Cost Delta

Llama 3.1 405B is estimated to save $403.75/month ($4,845/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    Llama 3.1 405B:Pick Llama 3.1 405B when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatLlama 3.1 405B

Lower output list price ($3.5/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5 Image

Larger window (400k).

Screenshots / visionLlama 3.1 405B

Llama 3.1 405B is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsinsufficient dataNeed SWE-bench on both sides.
High-volume chatLlama 3.1 405BLower output list price ($3.5/1M).
Voice / low-latency UIinsufficient dataNeed TTFT on both sides.
Long-document RAGOpenAI: GPT-5 ImageLarger window (400k).
Screenshots / visionLlama 3.1 405BLlama 3.1 405B is the side marked multimodal in the catalog.
Community Sentiment

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CompareLLM Matrix

Verified head-to-head card

LIVE
VS
OpenAI

OpenAI: GPT-5 Image

Elo n/a
LiveBench—
SWE-bench—
Speed—
Output cost$10/1M
Meta

Llama 3.1 405B

Elo 1,370
LiveBench61.2%
SWE-bench58.4%
Speed42 tok/s
Output cost$3.5/1M

Frequently Asked Questions

Which is better overall, OpenAI: GPT-5 Image or Llama 3.1 405B?
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, OpenAI: GPT-5 Image or Llama 3.1 405B?
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?
Llama 3.1 405B output tokens are $3.5/1M versus $10/1M. Input prices and retry rates still move the real bill.
Which is faster, OpenAI: GPT-5 Image or Llama 3.1 405B?
We do not have TTFT for both models.
Which has the larger context window?
OpenAI: GPT-5 Image accepts 400k tokens versus 128k.
Can I self-host either model?
Llama 3.1 405B is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
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. OpenAI: GPT-5 Image and Llama 3.1 405B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All OpenAI: GPT-5 Image matchups →|All Llama 3.1 405B matchups →
Llama 3.1 405B vs Llama 3.1 70B (next llama)GPT-5 vs Llama 3.1 405BLlama 4 Maverick vs Llama 3.1 405BGPT-4.5 Orion vs Llama 3.1 405BGPT-5.6 Sol vs Llama 3.1 405BGPT-5.6 Terra vs Llama 3.1 405B