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

Sao10K: Llama 3 8B Lunaris vs Qwen 2.5 Coder 32B benchmark

Name: Sao10K: Llama 3 8B Lunaris vs Qwen 2.5 Coder 32B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Sao10K: Llama 3 8B Lunaris (sao10k) and Qwen 2.5 Coder 32B (Alibaba) using the latest snapshots we have as of Aug 17, 2026. Sao10K: Llama 3 8B Lunaris wins on output price at $0.05/1M. Qwen 2.5 Coder 32B has the larger context window (131k 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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sao10k

Sao10K: Llama 3 8B Lunaris

Auto-discovered from OpenRouter (sao10k/l3-lunaris-8b). Preview until a second source matches.

$0.049999999999999996/1M out

Alibaba

Qwen 2.5 Coder 32B

Alibaba dedicated open-weight code generation model with near-frontier SWE-bench Verified coding capability.

Elo 1,425$0.72/1M out

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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.

Sao10K: Llama 3 8B Lunaris (2)vsQwen 2.5 Coder 32B (8)

Sao10K: Llama 3 8B Lunaris: 2W (20%)Overall: Qwen 2.5 Coder 32BQwen 2.5 Coder 32B: 8W (80%)

← Sao10K: Llama 3 8B LunarisQwen 2.5 Coder 32B →

Qwen 2.5 Coder 32B (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,425

Coding Elo

—vs1,495

SWE-bench

—vs65.2%

LiveBench

—vs64.8%

GPQA Diamond

—vs74%

Sao10K: Llama 3 8B Lunaris: 0WQwen 2.5 Coder 32B: 5W

Qwen 2.5 Coder 32B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs110 tok/s

Time to first token

—vs180 ms

Sao10K: Llama 3 8B Lunaris: 0WQwen 2.5 Coder 32B: 2W

Sao10K: Llama 3 8B Lunaris (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.05/1Mvs$0.72/1M

Input price

$0.04/1Mvs$0.18/1M

Context window

8kvs131k

Sao10K: Llama 3 8B Lunaris: 2WQwen 2.5 Coder 32B: 1W

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 AdvantageQwen 2.5 Coder 32B 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

Sao10K: Llama 3 8B Lunaris

$0.67/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,425

Code Elo

High is better

—

Code EloHigh is better

1,495

LiveBench

High is better

—

LiveBenchHigh is better

64.8%

SWE-bench

High is better

—

SWE-benchHigh is better

65.2%

GPQA

High is better

—

GPQAHigh is better

74%

TTFT

Low is better

—

TTFTLow is better

180 ms

Speed

High is better

—

SpeedHigh is better

110 tok/s

In $

Low is better

+350%$0.04 / 1M

In $Low is better

$0.18 / 1M

Out $

Low is better

+1340%$0.05 / 1M

Out $Low is better

$0.72 / 1M

Context

High is better

ContextHigh is better

131k+1500%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 87% with Sao10K: Llama 3 8B Lunaris

Monthly Volume50M tokens/mo

Quick Presets:

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

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

Sao10K: Llama 3 8B Lunaris$2.15 / mo

In: $1.4Out: $0.75

Qwen 2.5 Coder 32B$17.10 / mo

In: $6.3Out: $10.8

Estimated Cost Delta

Sao10K: Llama 3 8B Lunaris is estimated to save $14.95/month ($179/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Sao10K: Llama 3 8B Lunaris:Pick Sao10K: Llama 3 8B Lunaris when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatSao10K: Llama 3 8B Lunaris

Lower output list price ($0.05/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGQwen 2.5 Coder 32B

Larger window (131k).

Screenshots / visionQwen 2.5 Coder 32B

Qwen 2.5 Coder 32B 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	Sao10K: Llama 3 8B Lunaris	Lower output list price ($0.05/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Qwen 2.5 Coder 32B	Larger window (131k).
Screenshots / vision	Qwen 2.5 Coder 32B	Qwen 2.5 Coder 32B is the side marked multimodal in the catalog.

Community Sentiment

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CompareLLM Matrix

Verified head-to-head card

LIVE

sao10k

Sao10K: Llama 3 8B Lunaris

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0.05/1M

Alibaba

Qwen 2.5 Coder 32B

Elo 1,425

LiveBench64.8%

SWE-bench65.2%

Speed110 tok/s

Output cost$0.72/1M

Frequently Asked Questions

Which is better overall, Sao10K: Llama 3 8B Lunaris or Qwen 2.5 Coder 32B?: 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, Sao10K: Llama 3 8B Lunaris or Qwen 2.5 Coder 32B?: 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?: Sao10K: Llama 3 8B Lunaris output tokens are $0.05/1M versus $0.72/1M. Input prices and retry rates still move the real bill.
Which is faster, Sao10K: Llama 3 8B Lunaris or Qwen 2.5 Coder 32B?: We do not have TTFT for both models.
Which has the larger context window?: Qwen 2.5 Coder 32B accepts 131k tokens versus 8k.
Can I self-host either model?: Qwen 2.5 Coder 32B 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. Sao10K: Llama 3 8B Lunaris and Qwen 2.5 Coder 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Sao10K: Llama 3 8B Lunaris matchups →|All Qwen 2.5 Coder 32B matchups →

Qwen 2.5 Coder 32B vs Qwen 2.5 Plus (previous qwen)Qwen 2.5 Coder 32B vs Qwen3 235B (next qwen)Qwen 3 Max vs Qwen 2.5 Coder 32B Qwen QwQ 32B vs Qwen 2.5 Coder 32B Qwen3.8 27B vs Qwen 2.5 Coder 32B Qwen2.5 Coder 32B Instruct vs Qwen 2.5 Coder 32B

Sao10K: Llama 3 8B Lunaris vs Qwen 2.5 Coder 32B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Sao10K: Llama 3 8B Lunaris (2)vsQwen 2.5 Coder 32B (8)

Sao10K: Llama 3 8B Lunaris: 2W (20%)Overall: Qwen 2.5 Coder 32BQwen 2.5 Coder 32B: 8W (80%)

← Sao10K: Llama 3 8B LunarisQwen 2.5 Coder 32B →

Qwen 2.5 Coder 32B (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,425

Coding Elo

—vs1,495

SWE-bench

—vs65.2%

LiveBench

—vs64.8%

GPQA Diamond

—vs74%

Sao10K: Llama 3 8B Lunaris: 0WQwen 2.5 Coder 32B: 5W

Qwen 2.5 Coder 32B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs110 tok/s

Time to first token

—vs180 ms

Sao10K: Llama 3 8B Lunaris: 0WQwen 2.5 Coder 32B: 2W

Sao10K: Llama 3 8B Lunaris (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.05/1Mvs$0.72/1M

Input price

$0.04/1Mvs$0.18/1M

Context window

8kvs131k

Sao10K: Llama 3 8B Lunaris: 2WQwen 2.5 Coder 32B: 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatSao10K: Llama 3 8B Lunaris

Lower output list price ($0.05/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGQwen 2.5 Coder 32B

Larger window (131k).

Screenshots / visionQwen 2.5 Coder 32B

Qwen 2.5 Coder 32B 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	Sao10K: Llama 3 8B Lunaris	Lower output list price ($0.05/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Qwen 2.5 Coder 32B	Larger window (131k).
Screenshots / vision	Qwen 2.5 Coder 32B	Qwen 2.5 Coder 32B is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Sao10K: Llama 3 8B Lunaris or Qwen 2.5 Coder 32B?

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, Sao10K: Llama 3 8B Lunaris or Qwen 2.5 Coder 32B?

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?

Sao10K: Llama 3 8B Lunaris output tokens are $0.05/1M versus $0.72/1M. Input prices and retry rates still move the real bill.

Which is faster, Sao10K: Llama 3 8B Lunaris or Qwen 2.5 Coder 32B?

We do not have TTFT for both models.

Which has the larger context window?

Qwen 2.5 Coder 32B accepts 131k tokens versus 8k.

Can I self-host either model?

Qwen 2.5 Coder 32B 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. Sao10K: Llama 3 8B Lunaris and Qwen 2.5 Coder 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.