Pairwise benchmark snapshot · Aug 17, 2026

DeepSeek V3 vs Llama 3.1 405B benchmark

Name: DeepSeek V3 vs Llama 3.1 405B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

In this head-to-head showdown, Llama 3.1 405B delivers higher overall intelligence and human-preferred responses (Elo 1,370 vs 1,310), while Llama 3.1 405B leads in SWE-bench software engineering benchmarks (58.4%), while DeepSeek V3 is more budget-friendly at $1.029/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

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Executive Verdict Summary

Llama 3.1 405B holds empirical advantage (5 of 9 metrics)

Coding / SWESWE-bench

Llama 3.1 405BTop code solve rate

ReasoningGPQA / Live

Llama 3.1 405BTop logical accuracy

Best Value$/1M Tok

DeepSeek V3Lowest API billing cost

Speed / TokTok/Sec

DeepSeek V3Fastest stream rate

Verified Advantage Breakdown

9 benchmarks evaluated across capability, speed, and cost

DeepSeek V3 (4)Llama 3.1 405B (5)

DeepSeek V3

4 of 9 Wins

✓Output speed✓Input price✓Output price✓Context window

Llama 3.1 405B

5 of 9 Wins

✓Preference Elo✓LiveBench✓SWE-bench✓GPQA Diamond✓Time to first token

DeepSeek

Leads 4 of 9

DeepSeek V3

Prior DeepSeek flagship. Baseline for v3 vs v4.

Elo 1,310In: $0.257 · Out: $1.029/1M

Llama 3.1 405B

Δ 60 Arena Elo pts

Throughput LeaderDeepSeek V3 Wins

DeepSeek V3

66 tok/s

Value per Dollar LeaderDeepSeek V3 Wins

DeepSeek V3

$1.0287 / 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 standard models across 6 key capability dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect

0–100 %ile

Overall Matchup Breakdown

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

DeepSeek V3 (4)vsLlama 3.1 405B (6)

DeepSeek V3: 4W (40%)Llama 3.1 405B: 6W (60%)

← DeepSeek V3Llama 3.1 405B →

🏆Llama 3.1 405B Leads(5/5)

Intelligence & Reasoning

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

Benchmark

DeepSeek V3vsLlama 3.1 405B

Preference Elo

1,310vs1,370+60

Coding Elo

—vs1,385

SWE-bench

48.6%vs58.4%+9.8%

LiveBench

55.4%vs61.2%+5.8%

GPQA Diamond

59.1%vs75.2%+16.1%

DeepSeek V3: 0WLlama 3.1 405B: 5W

Tied (1-1)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark

DeepSeek V3vsLlama 3.1 405B

Output speed

66 tok/svs42 tok/s+24 tok/s

Time to first token

380 msvs360 ms+20 ms

DeepSeek V3: 1WLlama 3.1 405B: 1W

🏆DeepSeek V3 Leads(3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark

DeepSeek V3vsLlama 3.1 405B

Output price

$1.029/1Mvs$3.5/1M+$2.471/1M

Input price

$0.257/1Mvs$1.25/1M+$0.993/1M

Context window

164kvs128k+36k

DeepSeek V3: 3WLlama 3.1 405B: 0W

Side-by-Side Benchmark Matrix

DeepSeek V3Llama 3.1 405B

Preference EloLlama 3.1 405B +60

DeepSeek V31,310

Llama 3.1 405B1,370

Coding Elo

DeepSeek V3—

Llama 3.1 405B1,385

LiveBenchLlama 3.1 405B +5.8%

DeepSeek V355.4%

Llama 3.1 405B61.2%

SWE-benchLlama 3.1 405B +9.8%

DeepSeek V348.6%

Llama 3.1 405B58.4%

GPQA DiamondLlama 3.1 405B +16.1%

DeepSeek V359.1%

Llama 3.1 405B75.2%

Time to first tokenLlama 3.1 405B +20 ms

DeepSeek V3380 ms

Llama 3.1 405B360 ms

Output speedDeepSeek V3 +24 tok/s

DeepSeek V366 tok/s

Llama 3.1 405B42 tok/s

Input priceDeepSeek V3 +$0.993/1M

DeepSeek V3$0.257/1M

Llama 3.1 405B$1.25/1M

Output priceDeepSeek V3 +$2.471/1M

DeepSeek V3$1.029/1M

Llama 3.1 405B$3.5/1M

Context windowDeepSeek V3 +36k

DeepSeek V3164k

Llama 3.1 405B128k

Benchmark	DeepSeek V3	Llama 3.1 405B	Advantage Delta
Preference Elo	1,310 lmarena · Aug 17, 2026	1,370 lmarena · Aug 17, 2026	+60
Coding Elo	—	1,385 lmarena · Aug 17, 2026	—
LiveBench	55.4% livebench · Aug 17, 2026	61.2% livebench · Aug 17, 2026	+5.8%
SWE-bench	48.6% swebench · Aug 17, 2026	58.4% swebench · Aug 17, 2026	+9.8%
GPQA Diamond	59.1% seed-bootstrap · Aug 1, 2026	75.2% seed-bootstrap · Aug 1, 2026	+16.1%
Time to first token	380 ms seed-bootstrap · Aug 1, 2026	360 ms seed-bootstrap · Aug 1, 2026	+20 ms
Output speed	66 tok/s seed-bootstrap · Aug 1, 2026	42 tok/s seed-bootstrap · Aug 1, 2026	+24 tok/s
Input price	$0.257/1M openrouter · Aug 17, 2026	$1.25/1M seed-bootstrap · Aug 1, 2026	+$0.993/1M
Output price	$1.029/1M openrouter · Aug 17, 2026	$3.5/1M seed-bootstrap · Aug 1, 2026	+$2.471/1M
Context window	164k openrouter · Aug 17, 2026	128k seed-bootstrap · Aug 1, 2026	+36k

Workload Cost & Savings Calculator

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

Save 75% with DeepSeek V3

Monthly Volume50M tokens/mo

Quick Presets:

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

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

DeepSeek V3$24.44 / mo

In: $9.01Out: $15.43

Llama 3.1 405B$96.25 / mo

In: $43.75Out: $52.5

Estimated Cost Delta

DeepSeek V3 is estimated to save $71.81/month ($862/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Llama 3.1 405B:Pick Llama 3.1 405B when repo-level coding accuracy is the constraint.
2
DeepSeek V3:Pick DeepSeek V3 when you are optimizing output cost.
3
Llama 3.1 405B:Pick Llama 3.1 405B when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsLlama 3.1 405B

Higher SWE-bench (58.4%).

High-volume chatDeepSeek V3

Lower output list price ($1.029/1M).

Voice / low-latency UILlama 3.1 405B

Lower TTFT (360 ms).

Long-document RAGDeepSeek V3

Larger window (164k).

Screenshots / visionLlama 3.1 405B

Llama 3.1 405B is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Llama 3.1 405B	Higher SWE-bench (58.4%).
High-volume chat	DeepSeek V3	Lower output list price ($1.029/1M).
Voice / low-latency UI	Llama 3.1 405B	Lower TTFT (360 ms).
Long-document RAG	DeepSeek V3	Larger window (164k).
Screenshots / vision	Llama 3.1 405B	Llama 3.1 405B is the side marked multimodal in the catalog.

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK

DeepSeek

DeepSeek V3

Elo 1,310

SWE-bench48.6%

Speed (tok/s)66 tok/s

Input / 1M Tokens$0.257/1M

Output / 1M Tokens$1.029/1M

Llama 3.1 405B

Elo 1,370

SWE-bench58.4%

Speed (tok/s)42 tok/s

Input / 1M Tokens$1.25/1M

Output / 1M Tokens$3.5/1M

Frequently Asked Questions

Which is better overall, DeepSeek V3 or Llama 3.1 405B?: Llama 3.1 405B has the higher preference Elo in our latest snapshot (1,370). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, DeepSeek V3 or Llama 3.1 405B?: Llama 3.1 405B leads SWE-bench at 58.4% vs 48.6%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: DeepSeek V3 output tokens are $1.029/1M versus $3.5/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek V3 or Llama 3.1 405B?: Llama 3.1 405B has the lower time-to-first-token (360 ms vs 380 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: DeepSeek V3 accepts 164k tokens versus 128k.
Can I self-host either model?: Both DeepSeek V3 and Llama 3.1 405B are marked open-weights. Hosting cost is not in this table.
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 V3 and Llama 3.1 405B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All DeepSeek V3 matchups →|All Llama 3.1 405B matchups →

DeepSeek V3 vs DeepSeek Coder V2 (previous deepseek)DeepSeek V3 vs DeepSeek R1 (next deepseek)Llama 3.1 405B vs Llama 3.1 70B (next llama)Llama 4 Maverick vs Llama 3.1 405B DeepSeek V4 Pro vs Llama 3.1 405B DeepSeek V4 Flash vs Llama 3.1 405B

DeepSeek V3 vs Llama 3.1 405B benchmark

Capability Percentiles

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

Multi-Dimensional Capability Radar

Leaders Matchup Capability Radar

Comparing top standard models across 6 key capability dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect

0–100 %ile

Side-by-Side Benchmark Matrix

DeepSeek V3Llama 3.1 405B

Preference EloLlama 3.1 405B +60

DeepSeek V31,310

Llama 3.1 405B1,370

Coding Elo

DeepSeek V3—

Llama 3.1 405B1,385

LiveBenchLlama 3.1 405B +5.8%

DeepSeek V355.4%

Llama 3.1 405B61.2%

SWE-benchLlama 3.1 405B +9.8%

DeepSeek V348.6%

Llama 3.1 405B58.4%

GPQA DiamondLlama 3.1 405B +16.1%

DeepSeek V359.1%

Llama 3.1 405B75.2%

Time to first tokenLlama 3.1 405B +20 ms

DeepSeek V3380 ms

Llama 3.1 405B360 ms

Output speedDeepSeek V3 +24 tok/s

DeepSeek V366 tok/s

Llama 3.1 405B42 tok/s

Input priceDeepSeek V3 +$0.993/1M

DeepSeek V3$0.257/1M

Llama 3.1 405B$1.25/1M

Output priceDeepSeek V3 +$2.471/1M

DeepSeek V3$1.029/1M

Llama 3.1 405B$3.5/1M

Context windowDeepSeek V3 +36k

DeepSeek V3164k

Llama 3.1 405B128k

Benchmark

DeepSeek V3

Llama 3.1 405B

Advantage Delta

Preference Elo

1,310

lmarena · Aug 17, 2026

1,370

lmarena · Aug 17, 2026

+60

Coding Elo

—

1,385

lmarena · Aug 17, 2026

—

LiveBench

55.4%

livebench · Aug 17, 2026

61.2%

livebench · Aug 17, 2026

+5.8%

SWE-bench

48.6%

swebench · Aug 17, 2026

58.4%

swebench · Aug 17, 2026

+9.8%

GPQA Diamond

59.1%

seed-bootstrap · Aug 1, 2026

75.2%

seed-bootstrap · Aug 1, 2026

+16.1%

Time to first token

380 ms

seed-bootstrap · Aug 1, 2026

360 ms

seed-bootstrap · Aug 1, 2026

+20 ms

Output speed

66 tok/s

seed-bootstrap · Aug 1, 2026

42 tok/s

seed-bootstrap · Aug 1, 2026

+24 tok/s

Input price

$0.257/1M

openrouter · Aug 17, 2026

$1.25/1M

seed-bootstrap · Aug 1, 2026

+$0.993/1M

Output price

$1.029/1M

openrouter · Aug 17, 2026

$3.5/1M

seed-bootstrap · Aug 1, 2026

+$2.471/1M

Context window

164k

openrouter · Aug 17, 2026

128k

seed-bootstrap · Aug 1, 2026

+36k

Recommended Workload Routing

Repo / coding agentsLlama 3.1 405B

Higher SWE-bench (58.4%).

High-volume chatDeepSeek V3

Lower output list price ($1.029/1M).

Voice / low-latency UILlama 3.1 405B

Lower TTFT (360 ms).

Long-document RAGDeepSeek V3

Larger window (164k).

Screenshots / visionLlama 3.1 405B

Llama 3.1 405B is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Llama 3.1 405B	Higher SWE-bench (58.4%).
High-volume chat	DeepSeek V3	Lower output list price ($1.029/1M).
Voice / low-latency UI	Llama 3.1 405B	Lower TTFT (360 ms).
Long-document RAG	DeepSeek V3	Larger window (164k).
Screenshots / vision	Llama 3.1 405B	Llama 3.1 405B is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek V3 or Llama 3.1 405B?

Llama 3.1 405B has the higher preference Elo in our latest snapshot (1,370). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, DeepSeek V3 or Llama 3.1 405B?

Llama 3.1 405B leads SWE-bench at 58.4% vs 48.6%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

DeepSeek V3 output tokens are $1.029/1M versus $3.5/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek V3 or Llama 3.1 405B?

Llama 3.1 405B has the lower time-to-first-token (360 ms vs 380 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

DeepSeek V3 accepts 164k tokens versus 128k.

Can I self-host either model?

Both DeepSeek V3 and Llama 3.1 405B are marked open-weights. Hosting cost is not in this table.

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 V3 and Llama 3.1 405B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.