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Llama 3.1 8B Instruct vs Qwen3.8 Flash

Qwen3.8 Flash leads the LLM Stats Score 49.6 to -2.4. Llama 3.1 8B Instruct is 7.7x cheaper per token.

Meta · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3.8 Flash leads the overall LLM Stats Score 49.6 to -2.4, ranking #16 overall.

In the 1 individual benchmarks reported for both models, Qwen3.8 Flash wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, Llama 3.1 8B Instruct is roughly 7.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Qwen3.8 Flash also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Llama 3.1 8B Instruct

  • cost matters — it's about 7.7x cheaper per token
  • you need open weights you can self-host or fine-tune

Choose Qwen3.8 Flash

  • overall performance matters — it scores 49.6 and ranks #16 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you process long inputs — it offers a 1,000,000 token context window
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Core performance indexes
-2.4
#322
49.6
#16
-3.5
#321
49.2
#16
-2.2
#235
36.6
#20
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
$0.03 / M
$0.15 / M
Output price
$0.03 / M
$0.47 / M
Context window
131,072
1,000,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Llama 3.1 8B Instruct
Qwen3.8 Flash
-2.1#300
32.6#55
17.0#73
31.6#10
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

18 reported for Llama 3.1 8B Instruct · 22 for Qwen3.8 Flash

1 shared

Llama 3.1 8B Instruct outperforms in 0 benchmarks, while Qwen3.8 Flash is better at 1 benchmark (GPQA).

Qwen3.8 Flash significantly outperforms across most benchmarks.

Mon Aug 31 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Llama 3.1 8B Instruct costs less

For input processing, Llama 3.1 8B Instruct ($0.03/1M tokens) is 5.0x cheaper than Qwen3.8 Flash ($0.15/1M tokens).

For output processing, Llama 3.1 8B Instruct ($0.03/1M tokens) is 15.7x cheaper than Qwen3.8 Flash ($0.47/1M tokens).

In conclusion, Qwen3.8 Flash is more expensive than Llama 3.1 8B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Mon Aug 31 2026 • llm-stats.com
Meta
Llama 3.1 8B Instruct
Input tokens$0.03
Output tokens$0.03
Best providerLambda
Alibaba Cloud / Qwen Team
Qwen3.8 Flash
Input tokens$0.15
Output tokens$0.47
Best providerNovita
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

117.0B diff

Qwen3.8 Flash has 117.0B more parameters than Llama 3.1 8B Instruct, making it 1462.5% larger.

Meta
Llama 3.1 8B Instruct
8.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8 Flash
125.0Bparameters
8.0B
Llama 3.1 8B Instruct
125.0B
Qwen3.8 Flash

Context Window

Maximum input and output token capacity

Qwen3.8 Flash accepts 1,000,000 input tokens compared to Llama 3.1 8B Instruct's 131,072 tokens. Both models can generate responses up to 131,072 tokens.

Meta
Llama 3.1 8B Instruct
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3.8 Flash
Input1,000,000 tokens
Output131,072 tokens
Mon Aug 31 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.8 Flash supports multimodal inputs, whereas Llama 3.1 8B Instruct does not.

Qwen3.8 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

Llama 3.1 8B Instruct

Text
Images
Audio
Video

Qwen3.8 Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.1 8B Instruct is licensed under Llama 3.1 Community License, while Qwen3.8 Flash uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

Llama 3.1 8B Instruct

Llama 3.1 Community License

Open weights

Qwen3.8 Flash

Proprietary

Closed source

Release Timeline

When each model was launched

Llama 3.1 8B Instruct was released on 2024-07-23, while Qwen3.8 Flash was released on 2026-08-26.

Qwen3.8 Flash is 25 months newer than Llama 3.1 8B Instruct.

Llama 3.1 8B Instruct

Jul 23, 2024

2.1 years ago

Qwen3.8 Flash

Aug 26, 2026

5 days ago

2.1yr newer

Knowledge Cutoff

When training data ends

Llama 3.1 8B Instruct has a documented knowledge cutoff of 2023-12-31, while Qwen3.8 Flash's cutoff date is not specified.

We can confirm Llama 3.1 8B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without Qwen3.8 Flash's cutoff date.

Llama 3.1 8B Instruct

Dec 2023

Qwen3.8 Flash

Provider Availability

Llama 3.1 8B Instruct is available from Lambda, DeepInfra, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock. Qwen3.8 Flash is available from Novita.

Llama 3.1 8B Instruct

lambda logo
Lambda
Input Price:Input: $0.03/1MOutput Price:Output: $0.03/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.05/1MOutput Price:Output: $0.05/1M
groq logo
Groq
Input Price:Input: $0.05/1MOutput Price:Output: $0.08/1M
sambanova logo
Sambanova
Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M
cerebras logo
Cerebras
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
together logo
Together
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
fireworks logo
Fireworks
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.22/1MOutput Price:Output: $0.22/1M

Qwen3.8 Flash

novita logo
Novita
Input Price:Input: $0.15/1MOutput Price:Output: $0.47/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Llama 3.1 8B Instruct and Qwen3.8 Flash side-by-side, then vote on the output you prefer.

Llama 3.1 8B Instruct
✓ Preferred
Qwen3.8 Flash
Open in Playground

FAQ

Common questions about Llama 3.1 8B Instruct vs Qwen3.8 Flash.

Which is better, Llama 3.1 8B Instruct or Qwen3.8 Flash?

Qwen3.8 Flash leads the LLM Stats Score 49.6 to -2.4. Llama 3.1 8B Instruct is made by Meta and Qwen3.8 Flash is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Llama 3.1 8B Instruct compare to Qwen3.8 Flash in benchmarks?

Llama 3.1 8B Instruct scores GSM-8K (CoT): 84.5%, ARC-C: 83.4%, API-Bank: 82.6%, IFEval: 80.4%, BFCL: 76.1%. Qwen3.8 Flash scores MathVision: 95.7%, LiveCodeBench v6: 91.9%, GPQA: 91.7%, CharXiv-R: 90.6%, RealWorldQA: 88.5%.

Is Llama 3.1 8B Instruct cheaper than Qwen3.8 Flash?

Llama 3.1 8B Instruct is 5.0x cheaper for input tokens. Llama 3.1 8B Instruct costs $0.03/M input and $0.03/M output via lambda. Qwen3.8 Flash costs $0.15/M input and $0.47/M output via novita.

What are the context window sizes for Llama 3.1 8B Instruct and Qwen3.8 Flash?

Llama 3.1 8B Instruct supports 131K tokens and Qwen3.8 Flash supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Llama 3.1 8B Instruct and Qwen3.8 Flash?

Key differences include LLM Stats Score (-2.4 vs 49.6), context window (131K vs 1.0M), input pricing ($0.03 vs $0.15/M), multimodal support (no vs yes), licensing (Llama 3.1 Community License vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 3.1 8B Instruct and Qwen3.8 Flash?

Llama 3.1 8B Instruct is developed by Meta and Qwen3.8 Flash is developed by Alibaba Cloud / Qwen Team.