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Llama 3.1 8B Instruct vs Qwen3.8 Omni Flash

Signal-by-Signal Comparison
SignalLlama 3.1 8B InstructDeltaQwen3.8 Omni Flash
Capabilities
50
-33
83
Benchmarks
44
+44
0
Pricing
100
+0
100
Context window size
81
-14
95
Recency
0
-100
100
Output Capacity
81
-1
82
Overall Result
2 wins
of 6
4 wins
Qwen3.8 Omni Flash wins 4 of 6 signals

Score History

Score History (32 data points)
Llama 3.1 8B InstructQwen3.8 Omni Flash
Llama 3.1 8B Instruct

44.5

current score

Leader

Llama 3.1 8B Instruct

right now

Qwen3.8 Omni Flash

40

current score

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

Llama 3.1 8B Instruct

Meta

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

Qwen3.8 Omni Flash

Alibaba

Per request$0.000385
Daily$1.28
Monthly$38.50
Annual$462.00

Llama 3.1 8B Instruct saves you $29.50/month

That's $354.00/year compared to Qwen3.8 Omni Flash at your current usage level of 100K calls/month.

77% cheaper
Choose Llama 3.1 8B Instruct for cost optimization

Llama 3.1 8B Instruct pricing:
Input:$0.05/M tokens
Output:$0.08/M tokens
Qwen3.8 Omni Flash pricing:
Input:$0.15/M tokens
Output:$0.47/M tokens
Winner
Llama 3.1 8B Instruct

Meta

45

Composite Score

Qwen3.8 Omni Flash

Alibaba

40

Composite Score

Signal-by-Signal Comparison
MetricLlama 3.1 8B InstructQwen3.8 Omni FlashWinner
Overall Score
45
40
Llama 3.1 8B Instruct
Rank#232#246
Llama 3.1 8B Instruct
Quality Rank#232#246
Llama 3.1 8B Instruct
Adoption Rank#232#246
Llama 3.1 8B Instruct
Parameters8B----
Context Window131K1000K
Qwen3.8 Omni Flash
Pricing$0.05/$0.08/M$0.15/$0.47/M--
Signal Scores
Capabilities
50
83
Qwen3.8 Omni Flash
Benchmarks
44
--
Llama 3.1 8B Instruct
Pricing
100
100
Llama 3.1 8B Instruct
Context window size
81
95
Qwen3.8 Omni Flash
Recency
0
100
Qwen3.8 Omni Flash
Output Capacity
81
82
Qwen3.8 Omni Flash
Benchmark Head-to-Head(6 benchmarks)
Llama 3.1: 0Qwen3.8 Omni: 0
Llama 3.1
Qwen3.8 Omni
Normalized 0-100%
MMLU-Pro
30.37%-
HumanEval
69.5%-
IFEval
72.05%-
BBH
30.85%-
Arena Elo
1211-
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.

Llama 3.1 8B InstructEntry Level

Scores 45/100 (rank #232), placing it in the top 20% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Qwen3.8 Omni FlashEntry Level

Scores 40/100 (rank #246), placing it in the top 16% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 5-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 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

Choose Qwen3.8 Omni Flash when you need:

  • Processing long documents or large codebases (1000K token context)
  • Multimodal workflows that require image understanding
  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
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
Qwen3.8 Omni Flash
Input cost$0.15/M tokens
Output cost$0.47/M tokens
Cost per quality point$0.015
Est. monthly (1M tokens/day)$9.30

Llama 3.1 8B Instruct offers 79% better value per quality point. At 1M tokens/day, you'd spend $1.95/month with Llama 3.1 8B Instruct vs $9.30/month with Qwen3.8 Omni Flash - a $7.35 monthly difference.

Latency & Speed
Llama 3.1 8B InstructFaster
Speed score0/100
Qwen3.8 Omni Flash
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

Llama 3.1 8B Instruct

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

Llama 3.1 8B Instruct

Long document analysis

Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass

Qwen3.8 Omni Flash

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 (45/100) 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

Qwen3.8 Omni Flash
Which Should You Choose?
Our recommendation:
Llama 3.1 8B Instruct

Llama 3.1 8B Instruct has a moderate advantage with a 4.5-point lead in composite score. It wins on more signal dimensions, but Qwen3.8 Omni Flash has specific strengths that could make it the better choice for certain workflows.

by Meta

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 79% lower pricing; better value at scale
  • 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 Alibaba

Consider for specialized use cases.

Capability Comparison
CapabilityLlama 3.1 8B InstructQwen3.8 Omni Flash
Vision (Image Input)differs
Function Calling
Streaming
JSON Mode
Reasoningdiffers
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Llama 3.1 8B Instruct

Meta

Best Value
$0.1860
estimated monthly cost

Qwen3.8 Omni Flash

Alibaba

$0.8340
estimated monthly cost

Llama 3.1 8B Instruct saves you $0.6480/month

That's 78% cheaper than Qwen3.8 Omni Flash 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
ParameterLlama 3.1 8B InstructQwen3.8 Omni Flash
Context Window131K1M
Max Output Tokens117,964131,072
Open SourceYesNo
CreatedJul 23, 2024Sep 21, 2026
Last updated: 39m ago

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Llama 3.1 8B Instruct vs Qwen3.8 Omni Flash (2026) | LM Market Cap