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Ling 3.1 Flash vs Llama 3.1 8B Instruct

Ling 3.1 Flash

inclusionai

40#238
vs
Signal-by-Signal Comparison
SignalLing 3.1 FlashDeltaLlama 3.1 8B Instruct
Capabilities
50
--
50
Pricing
100
+0
100
Context window size
86
+5
81
Recency
100
+100
0
Output Capacity
72
-9
81
Benchmarks
0
-44
44
Overall Result
3 wins
of 6
2 wins
Ling 3.1 Flash wins 3 of 6 signals

Score History

Score History (33 data points)
Ling 3.1 FlashLlama 3.1 8B Instruct
Ling 3.1 Flash

40

current score

Leader

Llama 3.1 8B Instruct

right now

Llama 3.1 8B Instruct

44.5

current score

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

Ling 3.1 Flash

inclusionai

Best Value
Per request$0.000000
Daily$0.00
Monthly$0.00
Annual$0.00

Llama 3.1 8B Instruct

Meta

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

Ling 3.1 Flash saves you $9.00/month

That's $108.00/year compared to Llama 3.1 8B Instruct at your current usage level of 100K calls/month.

100% cheaper
Choose Ling 3.1 Flash for cost optimization

Ling 3.1 Flash pricing:
Input:$0.00/M tokens
Output:$0.00/M tokens
Llama 3.1 8B Instruct pricing:
Input:$0.05/M tokens
Output:$0.08/M tokens
Ling 3.1 Flash

inclusionai

40

Composite Score

Winner
Llama 3.1 8B Instruct

Meta

45

Composite Score

Signal-by-Signal Comparison
MetricLing 3.1 FlashLlama 3.1 8B InstructWinner
Overall Score
40
45
Llama 3.1 8B Instruct
Rank#238#236
Llama 3.1 8B Instruct
Quality Rank#238#236
Llama 3.1 8B Instruct
Adoption Rank#238#236
Llama 3.1 8B Instruct
Parameters--8B--
Context Window262K131K
Ling 3.1 Flash
PricingFree$0.05/$0.08/M--
Signal Scores
Capabilities
50
50
Ling 3.1 Flash
Pricing
100
100
Ling 3.1 Flash
Context window size
86
81
Ling 3.1 Flash
Recency
100
0
Ling 3.1 Flash
Output Capacity
72
81
Llama 3.1 8B Instruct
Benchmarks--
44
Llama 3.1 8B Instruct
Benchmark Head-to-Head(6 benchmarks)
Ling 3.1: 0Llama 3.1: 0
Ling 3.1
Llama 3.1
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.

Ling 3.1 FlashEntry Level

Scores 40/100 (rank #238), placing it in the top 18% of all 290 models tracked.

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

Scores 45/100 (rank #236), placing it in the top 19% 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 Ling 3.1 Flash when you need:

  • High-volume production workloads where API costs must be minimized
  • Processing long documents or large codebases (262K token context)
  • Step-by-step reasoning and chain-of-thought problem solving

Choose Llama 3.1 8B Instruct when you need:

  • Self-hosted deployments where you need full control over the model
Cost-Performance Analysis
Ling 3.1 Flash
Input cost$0.00/M tokens
Output cost$0.00/M tokens
Cost per quality point$0.000
Est. monthly (1M tokens/day)$0.00
Llama 3.1 8B Instruct
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

Compare the cost per quality point to find the best value for your specific workload.

Latency & Speed
Ling 3.1 FlashFaster
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

Ling 3.1 Flash

Customer support chatbot

Suitable for user-facing chat with competitive response times. Ling 3.1 Flash also offers lower per-token costs for high-volume support

Ling 3.1 Flash

Long document analysis

Larger context window (262K tokens) can process longer documents, contracts, and research papers in a single pass

Ling 3.1 Flash

Batch data extraction

Lower output pricing ($0.00/M) reduces costs when processing thousands of records daily

Ling 3.1 Flash

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
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 Ling 3.1 Flash has specific strengths that could make it the better choice for certain workflows.

by inclusionai

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 100% 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 Meta

Consider for specialized use cases.

Capability Comparison
CapabilityLing 3.1 FlashLlama 3.1 8B Instruct
Vision (Image Input)
Function Calling
Streaming
JSON Modediffers
Reasoningdiffers
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Ling 3.1 Flash

inclusionai

Best Value
$0.000000
estimated monthly cost

Llama 3.1 8B Instruct

Meta

$0.1860
estimated monthly cost

Ling 3.1 Flash saves you $0.1860/month

That's 100% cheaper than Llama 3.1 8B Instruct 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
ParameterLing 3.1 FlashLlama 3.1 8B Instruct
Context Window262K131K
Max Output Tokens32,768117,964
Open SourceNoYes
CreatedOct 2, 2026Jul 23, 2024
Last updated: 52m ago

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Ling 3.1 Flash vs Llama 3.1 8B Instruct (2026) | LM Market Cap