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

DeepSeek: DeepSeek V3 0324 vs Llama 3.1 70B benchmark

Name: DeepSeek: DeepSeek V3 0324 vs Llama 3.1 70B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

In this head-to-head showdown, Llama 3.1 70B is more budget-friendly at $0.4/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

Share Analysis:

Verified Head-to-Head Advantage Breakdown

3 direct benchmark disciplines evaluated across capability, speed, and cost

DeepSeek: DeepSeek V3 0324 (2)Llama 3.1 70B (1)

DeepSeek: DeepSeek V3 0324

2 of 3 Wins

✓Input price✓Context window

Llama 3.1 70B

1 of 3 Wins

✓Output price

DeepSeek

Leads 2 of 3 metrics

DeepSeek: DeepSeek V3 0324

Auto-discovered from OpenRouter (deepseek/deepseek-chat-v3-0324). Preview until a second source matches.

$1.12/1M out

No shared data

Single model data

Throughput Leader

No shared data

No latency data

Value per Dollar LeaderLlama 3.1 70B Wins

Llama 3.1 70B

$0.39999999999999997 / 1M output

Capability Percentiles

Relative percentile scores computed across all active models in the benchmark catalog.

Multi-Dimensional Capability Radar

Leaders Matchup Capability Radar

Comparing top Western standard models with China's leading frontier rival across 6 skill dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect

0–100 %ile

Head-to-Head Comparison

Overall Matchup Breakdown

Category wins across reasoning intelligence, generation speed, and token cost.

DeepSeek: DeepSeek V3 0324 (2)vsLlama 3.1 70B (7)

DeepSeek: DeepSeek V3 0324: 2W (22%)Overall: Llama 3.1 70BLlama 3.1 70B: 7W (78%)

← DeepSeek: DeepSeek V3 0324Llama 3.1 70B →

🏆Llama 3.1 70B(4/5)

Intelligence & Reasoning

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

Benchmark

DeepSeek: DeepSeek V3 0324vsLlama 3.1 70B

Preference Elo

—vs1,240

Coding Elo

—vs—

SWE-bench

—vs40.2%

LiveBench

—vs46.8%

GPQA Diamond

—vs48%

DeepSeek: DeepSeek V3 0324: 0WLlama 3.1 70B: 4W

🏆Llama 3.1 70B(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark

DeepSeek: DeepSeek V3 0324vsLlama 3.1 70B

Output speed

—vs125 tok/s

Time to first token

—vs170 ms

DeepSeek: DeepSeek V3 0324: 0WLlama 3.1 70B: 2W

🏆DeepSeek: DeepSeek V3 0324(2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark

DeepSeek: DeepSeek V3 0324vsLlama 3.1 70B

Output price

$1.12/1Mvs$0.4/1M+$0.72/1M

Input price

$0.27/1Mvs$0.4/1M+$0.13/1M

Context window

164kvs131k+33k

DeepSeek: DeepSeek V3 0324: 2WLlama 3.1 70B: 1W

Side-by-Side Benchmark Matrix

Preference Elo

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B1,240

lmarena · Aug 17, 2026

LiveBench

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B46.8%

livebench · Aug 17, 2026

SWE-bench

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B40.2%

swebench · Aug 17, 2026

GPQA Diamond

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B48%

seed-bootstrap · Aug 1, 2026

Time to first token

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B170 ms

seed-bootstrap · Aug 1, 2026

Output speed

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B125 tok/s

seed-bootstrap · Aug 1, 2026

Input price+$0.13/1M

DeepSeek: DeepSeek V3 0324$0.27/1M

openrouter · Aug 17, 2026

Llama 3.1 70B$0.4/1M

openrouter · Aug 17, 2026

Output price+$0.72/1M

DeepSeek: DeepSeek V3 0324$1.12/1M

openrouter · Aug 17, 2026

Llama 3.1 70B$0.4/1M

openrouter · Aug 17, 2026

Context window+33k

DeepSeek: DeepSeek V3 0324164k

openrouter · Aug 17, 2026

Llama 3.1 70B131k

openrouter · Aug 17, 2026

Benchmark	DeepSeek: DeepSeek V3 0324	Llama 3.1 70B	Advantage Delta
Preference Elo	—	1,240 lmarena · Aug 17, 2026	—
LiveBench	—	46.8% livebench · Aug 17, 2026	—
SWE-bench	—	40.2% swebench · Aug 17, 2026	—
GPQA Diamond	—	48% seed-bootstrap · Aug 1, 2026	—
Time to first token	—	170 ms seed-bootstrap · Aug 1, 2026	—
Output speed	—	125 tok/s seed-bootstrap · Aug 1, 2026	—
Input price	$0.27/1M openrouter · Aug 17, 2026	$0.4/1M openrouter · Aug 17, 2026	+$0.13/1M
Output price	$1.12/1M openrouter · Aug 17, 2026	$0.4/1M openrouter · Aug 17, 2026	+$0.72/1M
Context window	164k openrouter · Aug 17, 2026	131k openrouter · Aug 17, 2026	+33k

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 24% with Llama 3.1 70B

Monthly Volume50M tokens/mo

Quick Presets:

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

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

DeepSeek: DeepSeek V3 0324$26.25 / mo

In: $9.45Out: $16.8

Llama 3.1 70B$20.00 / mo

In: $14Out: $6

Estimated Cost Delta

Llama 3.1 70B is estimated to save $6.25/month ($75/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Llama 3.1 70B:Pick Llama 3.1 70B when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatLlama 3.1 70B

Lower output list price ($0.4/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGDeepSeek: DeepSeek V3 0324

Larger window (164k).

Screenshots / visionLlama 3.1 70B

Llama 3.1 70B 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	Llama 3.1 70B	Lower output list price ($0.4/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	DeepSeek: DeepSeek V3 0324	Larger window (164k).
Screenshots / vision	Llama 3.1 70B	Llama 3.1 70B is the side marked multimodal in the catalog.

Community Sentiment

Cast Your Matchup Vote

0 total votes

Community Discussions (0)

No comments posted on this matchup yet. Be the first to share an evaluation note!

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK

DeepSeek

DeepSeek: DeepSeek V3 0324

Elo n/a

SWE-bench—

Speed (tok/s)164k

Input / 1M Tokens$0.27/1M

Output / 1M Tokens$1.12/1M

Llama 3.1 70B

Elo 1,240

SWE-bench40.2%

Speed (tok/s)125 tok/s

Input / 1M Tokens$0.4/1M

Output / 1M Tokens$0.4/1M

Frequently Asked Questions

Which is better overall, DeepSeek: DeepSeek V3 0324 or Llama 3.1 70B?: 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, DeepSeek: DeepSeek V3 0324 or Llama 3.1 70B?: 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?: Llama 3.1 70B output tokens are $0.4/1M versus $1.12/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek: DeepSeek V3 0324 or Llama 3.1 70B?: We do not have TTFT for both models.
Which has the larger context window?: DeepSeek: DeepSeek V3 0324 accepts 164k tokens versus 131k.
Can I self-host either model?: Llama 3.1 70B 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. DeepSeek: DeepSeek V3 0324 and Llama 3.1 70B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All DeepSeek: DeepSeek V3 0324 matchups →|All Llama 3.1 70B matchups →

Llama 3.1 70B vs Llama 3.1 405B (previous llama)Llama 3.1 70B vs Llama 3.3 70B (next llama)DeepSeek V4 Pro vs Llama 3.1 70B Llama 4 Maverick vs Llama 3.1 70B DeepSeek V4 Flash vs Llama 3.1 70B DeepSeek R1 vs Llama 3.1 70B

Capability Percentiles

Relative percentile scores computed across all active models in the benchmark catalog.

Multi-Dimensional Capability Radar

Leaders Matchup Capability Radar

Comparing top Western standard models with China's leading frontier rival across 6 skill dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect

0–100 %ile

Side-by-Side Benchmark Matrix

Preference Elo

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B1,240

lmarena · Aug 17, 2026

LiveBench

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B46.8%

livebench · Aug 17, 2026

SWE-bench

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B40.2%

swebench · Aug 17, 2026

GPQA Diamond

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B48%

seed-bootstrap · Aug 1, 2026

Time to first token

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B170 ms

seed-bootstrap · Aug 1, 2026

Output speed

DeepSeek: DeepSeek V3 0324—

Llama 3.1 70B125 tok/s

seed-bootstrap · Aug 1, 2026

Input price+$0.13/1M

DeepSeek: DeepSeek V3 0324$0.27/1M

openrouter · Aug 17, 2026

Llama 3.1 70B$0.4/1M

openrouter · Aug 17, 2026

Output price+$0.72/1M

DeepSeek: DeepSeek V3 0324$1.12/1M

openrouter · Aug 17, 2026

Llama 3.1 70B$0.4/1M

openrouter · Aug 17, 2026

Context window+33k

DeepSeek: DeepSeek V3 0324164k

openrouter · Aug 17, 2026

Llama 3.1 70B131k

openrouter · Aug 17, 2026

Benchmark

DeepSeek: DeepSeek V3 0324

Llama 3.1 70B

Advantage Delta

Preference Elo

—

1,240

lmarena · Aug 17, 2026

—

LiveBench

—

46.8%

livebench · Aug 17, 2026

—

SWE-bench

—

40.2%

swebench · Aug 17, 2026

—

GPQA Diamond

—

48%

seed-bootstrap · Aug 1, 2026

—

Time to first token

—

170 ms

seed-bootstrap · Aug 1, 2026

—

Output speed

—

125 tok/s

seed-bootstrap · Aug 1, 2026

—

Input price

$0.27/1M

openrouter · Aug 17, 2026

$0.4/1M

openrouter · Aug 17, 2026

+$0.13/1M

Output price

$1.12/1M

openrouter · Aug 17, 2026

$0.4/1M

openrouter · Aug 17, 2026

+$0.72/1M

Context window

164k

openrouter · Aug 17, 2026

131k

openrouter · Aug 17, 2026

+33k

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatLlama 3.1 70B

Lower output list price ($0.4/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGDeepSeek: DeepSeek V3 0324

Larger window (164k).

Screenshots / visionLlama 3.1 70B

Llama 3.1 70B 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	Llama 3.1 70B	Lower output list price ($0.4/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	DeepSeek: DeepSeek V3 0324	Larger window (164k).
Screenshots / vision	Llama 3.1 70B	Llama 3.1 70B is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek: DeepSeek V3 0324 or Llama 3.1 70B?

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, DeepSeek: DeepSeek V3 0324 or Llama 3.1 70B?

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?

Llama 3.1 70B output tokens are $0.4/1M versus $1.12/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek: DeepSeek V3 0324 or Llama 3.1 70B?

We do not have TTFT for both models.

Which has the larger context window?

DeepSeek: DeepSeek V3 0324 accepts 164k tokens versus 131k.

Can I self-host either model?

Llama 3.1 70B 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. DeepSeek: DeepSeek V3 0324 and Llama 3.1 70B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.