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DeepSeek V3.2 Exp vs Llama 3.1 70B Instruct

DeepSeek V3.2 Exp

DeepSeek

72#105
vs
Signal-by-Signal Comparison
SignalDeepSeek V3.2 ExpDeltaLlama 3.1 70B Instruct
Capabilities
67
+50
17
Pricing
100
+0
99
Context window size
83
+2
81
Recency
59
+59
0
Output Capacity
83
+20
63
Benchmarks
0
-72
72
Overall Result
5 wins
of 6
1 wins
DeepSeek V3.2 Exp wins 5 of 6 signals

Score History

Score History (38 data points)
DeepSeek V3.2 ExpLlama 3.1 70B Instruct
DeepSeek V3.2 Exp

71.8

current score

Leader

DeepSeek V3.2 Exp

right now

Llama 3.1 70B Instruct

63.6

current score

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

DeepSeek V3.2 Exp

DeepSeek

Best Value
Per request$0.000475
Daily$1.58
Monthly$47.50
Annual$570.00

Llama 3.1 70B Instruct

Meta

Per request$0.001080
Daily$3.60
Monthly$108.00
Annual$1296.00

DeepSeek V3.2 Exp saves you $60.50/month

That's $726.00/year compared to Llama 3.1 70B Instruct at your current usage level of 100K calls/month.

56% cheaper
Choose DeepSeek V3.2 Exp for cost optimization

DeepSeek V3.2 Exp pricing:
Input:$0.27/M tokens
Output:$0.41/M tokens
Llama 3.1 70B Instruct pricing:
Input:$0.72/M tokens
Output:$0.72/M tokens
Winner
DeepSeek V3.2 Exp

DeepSeek

72

Composite Score

Llama 3.1 70B Instruct

Meta

64

Composite Score

Signal-by-Signal Comparison
MetricDeepSeek V3.2 ExpLlama 3.1 70B InstructWinner
Overall Score
72
64
DeepSeek V3.2 Exp
Rank#105#155
DeepSeek V3.2 Exp
Quality Rank#105#155
DeepSeek V3.2 Exp
Adoption Rank#105#155
DeepSeek V3.2 Exp
Parameters--70B--
Context Window164K131K
DeepSeek V3.2 Exp
Pricing$0.27/$0.41/M$0.72/$0.72/M--
Signal Scores
Capabilities
67
17
DeepSeek V3.2 Exp
Pricing
100
99
DeepSeek V3.2 Exp
Context window size
83
81
DeepSeek V3.2 Exp
Recency
59
0
DeepSeek V3.2 Exp
Output Capacity
83
63
DeepSeek V3.2 Exp
Benchmarks--
72
Llama 3.1 70B Instruct
Benchmark Head-to-Head(15 benchmarks)
DeepSeek V3.2: 11Llama 3.1: 0
DeepSeek V3.2
Llama 3.1
Normalized 0-100%
MMLU
88.5%86%
MMLU-Pro
75.9%62.8%
GPQA Diamond
59.1%46.7%
MATH-500
90.2%68%
HumanEval
82.6%80.5%
SWE-bench Verified
42%-
AIME 2024
39.2%-
GSM8K
96.7%95.1%
IFEval
87.1%83.6%
BBH
87.5%81.2%
ARC-Challenge
-94.8%
HellaSwag
-94.8%
Arena Elo
13181198
LiveBench
60.4%53.3%
BigCodeBench
50%46.1%
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.

DeepSeek V3.2 ExpStrong Performer

Scores 72/100 (rank #105), placing it in the top 64% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Llama 3.1 70B InstructCompetitive

Scores 64/100 (rank #155), placing it in the top 47% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

DeepSeek V3.2 Exp has a 8-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.

When to Use Each Model

Choose DeepSeek V3.2 Exp when you need:

  • High-volume production workloads where API costs must be minimized
  • Agentic applications using tool/function calling
  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model

Choose Llama 3.1 70B Instruct when you need:

  • Self-hosted deployments where you need full control over the model
Cost-Performance Analysis
DeepSeek V3.2 ExpBest Value
Input cost$0.27/M tokens
Output cost$0.41/M tokens
Cost per quality point$0.009
Est. monthly (1M tokens/day)$10.20
Llama 3.1 70B Instruct
Input cost$0.72/M tokens
Output cost$0.72/M tokens
Cost per quality point$0.023
Est. monthly (1M tokens/day)$21.60

DeepSeek V3.2 Exp offers 53% better value per quality point. At 1M tokens/day, you'd spend $10.20/month with DeepSeek V3.2 Exp vs $21.60/month with Llama 3.1 70B Instruct - a $11.40 monthly difference.

Latency & Speed
DeepSeek V3.2 ExpFaster
Speed score0/100
Llama 3.1 70B 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

DeepSeek V3.2 Exp

Customer support chatbot

Suitable for user-facing chat with competitive response times. DeepSeek V3.2 Exp also offers lower per-token costs for high-volume support

DeepSeek V3.2 Exp

Long document analysis

Larger context window (164K tokens) can process longer documents, contracts, and research papers in a single pass

DeepSeek V3.2 Exp

Batch data extraction

Lower output pricing ($0.41/M) reduces costs when processing thousands of records daily

DeepSeek V3.2 Exp

Creative writing & content

Higher overall composite score (72/100) correlates with better nuance, coherence, and style in long-form content

DeepSeek V3.2 Exp
Which Should You Choose?
Our recommendation:
DeepSeek V3.2 Exp

DeepSeek V3.2 Exp has a moderate advantage with a 8.199999999999996-point lead in composite score. It wins on more signal dimensions, but Llama 3.1 70B Instruct has specific strengths that could make it the better choice for certain workflows.

by DeepSeek

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 53% 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
CapabilityDeepSeek V3.2 ExpLlama 3.1 70B Instruct
Vision (Image Input)
Function Callingdiffers
Streaming
JSON Modediffers
Reasoningdiffers
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

DeepSeek V3.2 Exp

DeepSeek

Best Value
$0.9780
estimated monthly cost

Llama 3.1 70B Instruct

Meta

$2.16
estimated monthly cost

DeepSeek V3.2 Exp saves you $1.18/month

That's 55% cheaper than Llama 3.1 70B 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
ParameterDeepSeek V3.2 ExpLlama 3.1 70B Instruct
Context Window164K131K
Max Output Tokens147,4568,192
Open SourceYesYes
CreatedSep 29, 2025Jul 23, 2024
Last updated: 2m ago

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