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GPT-6 Luna Pro (batch) vs Llama 3.1 8B Instruct

Signal-by-Signal Comparison
SignalGPT-6 Luna Pro (batch)DeltaLlama 3.1 8B Instruct
Capabilities
100
+50
50
Pricing
100
0
100
Context window size
96
+14
81
Recency
100
+100
0
Output Capacity
82
+1
81
Benchmarks
0
-42
42
Overall Result
4 wins
of 6
2 wins
GPT-6 Luna Pro (batch) wins 4 of 6 signals

Score History

Score History (38 data points)
GPT-6 Luna Pro (batch)Llama 3.1 8B Instruct
GPT-6 Luna Pro (batch)

40

current score

Leader

Llama 3.1 8B Instruct

right now

Llama 3.1 8B Instruct

40.7

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

GPT-6 Luna Pro (batch)

OpenAI

Per request$0.000175
Daily$0.58
Monthly$17.50
Annual$210.00

Llama 3.1 8B Instruct

Meta

Best Value
Per request$0.000090
Daily$0.30
Monthly$9.00
Annual$108.00

Llama 3.1 8B Instruct saves you $8.50/month

That's $102.00/year compared to GPT-6 Luna Pro (batch) at your current usage level of 100K calls/month.

49% cheaper
Choose Llama 3.1 8B Instruct for cost optimization

GPT-6 Luna Pro (batch) pricing:
Input:$0.05/M tokens
Output:$0.25/M tokens
Llama 3.1 8B Instruct pricing:
Input:$0.05/M tokens
Output:$0.08/M tokens
GPT-6 Luna Pro (batch)

OpenAI

40

Composite Score

Winner
Llama 3.1 8B Instruct

Meta

41

Composite Score

Signal-by-Signal Comparison
MetricGPT-6 Luna Pro (batch)Llama 3.1 8B InstructWinner
Overall Score
40
41
Llama 3.1 8B Instruct
Rank#222#171
Llama 3.1 8B Instruct
Quality Rank#222#171
Llama 3.1 8B Instruct
Adoption Rank#222#171
Llama 3.1 8B Instruct
Parameters--8B--
Context Window1050K131K
GPT-6 Luna Pro (batch)
Pricing$0.05/$0.25/M$0.05/$0.08/M--
Signal Scores
Capabilities
100
50
GPT-6 Luna Pro (batch)
Pricing
100
100
Llama 3.1 8B Instruct
Context window size
96
81
GPT-6 Luna Pro (batch)
Recency
100
0
GPT-6 Luna Pro (batch)
Output Capacity
82
81
GPT-6 Luna Pro (batch)
Benchmarks--
42
Llama 3.1 8B Instruct
Benchmark Head-to-Head(5 benchmarks)
GPT-6 Luna: 0Llama 3.1: 0
GPT-6 Luna
Llama 3.1
Normalized 0-100%
MMLU-Pro
-30.37%
HumanEval
-69.5%
IFEval
-72.05%
BBH
-30.85%
BigCodeBench
-32.8%
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

GPT-6 Luna Pro (batch)Entry Level

Scores 40/100 (rank #222), placing it in the top 24% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Llama 3.1 8B InstructEntry Level

Scores 41/100 (rank #171), placing it in the top 41% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 1-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose GPT-6 Luna Pro (batch) when you need:

  • Processing long documents or large codebases (1050K token context)
  • Multimodal workflows that require image understanding
  • Step-by-step reasoning and chain-of-thought problem solving

Choose Llama 3.1 8B Instruct when you need:

  • High-volume production workloads where API costs must be minimized
  • Self-hosted deployments where you need full control over the model
Cost-Performance Analysis
GPT-6 Luna Pro (batch)
Input cost$0.05/M tokens
Output cost$0.25/M tokens
Cost per quality point$0.007
Est. monthly (1M tokens/day)$4.50
Llama 3.1 8B InstructBest Value
Input cost$0.05/M tokens
Output cost$0.08/M tokens
Cost per quality point$0.003
Est. monthly (1M tokens/day)$1.95

Llama 3.1 8B Instruct offers 57% better value per quality point. At 1M tokens/day, you'd spend $1.95/month with Llama 3.1 8B Instruct vs $4.50/month with GPT-6 Luna Pro (batch) - a $2.55 monthly difference.

Latency & Speed
GPT-6 Luna Pro (batch)Faster
Speed score0/100
Llama 3.1 8B Instruct
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

GPT-6 Luna Pro (batch)

Customer support chatbot

Suitable for user-facing chat with competitive response times. Llama 3.1 8B Instruct also offers lower per-token costs for high-volume support

GPT-6 Luna Pro (batch)

Long document analysis

Larger context window (1050K tokens) can process longer documents, contracts, and research papers in a single pass

GPT-6 Luna Pro (batch)

Batch data extraction

Lower output pricing ($0.08/M) reduces costs when processing thousands of records daily

Llama 3.1 8B Instruct

Creative writing & content

Higher overall composite score (41/100) correlates with better nuance, coherence, and style in long-form content

Llama 3.1 8B Instruct

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

GPT-6 Luna Pro (batch)
Which Should You Choose?
Our recommendation:
Llama 3.1 8B Instruct

GPT-6 Luna Pro (batch) and Llama 3.1 8B Instruct are extremely close in overall performance (only 0.7000000000000028 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

by OpenAI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by Meta

  • Choose for Cost - 57% lower pricing; better value at scale
Capability Comparison
CapabilityGPT-6 Luna Pro (batch)Llama 3.1 8B Instruct
Vision (Image Input)differs
Function Calling
Streaming
JSON Mode
Reasoningdiffers
Web Searchdiffers
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

GPT-6 Luna Pro (batch)

OpenAI

$0.3900
estimated monthly cost

Llama 3.1 8B Instruct

Meta

Best Value
$0.1860
estimated monthly cost

Llama 3.1 8B Instruct saves you $0.2040/month

That's 52% cheaper than GPT-6 Luna Pro (batch) at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterGPT-6 Luna Pro (batch)Llama 3.1 8B Instruct
Context Window1.1M131K
Max Output Tokens128,000117,964
Open SourceNoYes
CreatedSep 22, 2026Jul 23, 2024
Last updated: 24m ago

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GPT-6 Luna Pro (batch) vs Llama 3.1 8B Instruct (2026) | LM Market Cap