Pairwise benchmark snapshot · Aug 17, 2026

DeepSeek Coder V2 vs Llama 3.1 70B benchmark

Name: DeepSeek Coder V2 vs Llama 3.1 70B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek Coder V2 (DeepSeek) and Llama 3.1 70B (Meta) using the latest snapshots we have as of Aug 17, 2026. On preference Elo, DeepSeek Coder V2 is ahead by 125 points (1,365 vs 1,240; lmarena (Aug 17, 2026)). On SWE-bench coding, DeepSeek Coder V2 resolves 60.5% versus 40.2% (swebench (Aug 17, 2026)). Llama 3.1 70B streams faster (125 tok/s) while DeepSeek Coder V2 is the cheaper output token ($0.28/1M). Llama 3.1 70B has the larger context window (131k tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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DeepSeek

DeepSeek Coder V2

DeepSeek open-weight Mixture-of-Experts coding model supporting 338 programming languages and 128k context.

Elo 1,365$0.28/1M out

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Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek Coder V2 (7)vsLlama 3.1 70B (3)

DeepSeek Coder V2: 7W (70%)Overall: DeepSeek Coder V2Llama 3.1 70B: 3W (30%)

← DeepSeek Coder V2Llama 3.1 70B →

DeepSeek Coder V2 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,365vs1,240

Coding Elo

1,442vs—

SWE-bench

60.5%vs40.2%

LiveBench

58.6%vs46.8%

GPQA Diamond

70.2%vs48%

DeepSeek Coder V2: 5WLlama 3.1 70B: 0W

Llama 3.1 70B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

75 tok/svs125 tok/s

Time to first token

290 msvs170 ms

DeepSeek Coder V2: 0WLlama 3.1 70B: 2W

DeepSeek Coder V2 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.28/1Mvs$0.4/1M

Input price

$0.14/1Mvs$0.4/1M

Context window

128kvs131k

DeepSeek Coder V2: 2WLlama 3.1 70B: 1W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageDeepSeek Coder V2 4/6

Preference Elo

DeepSeek Coder V2

125 pts advantage

Throughput Speed

Llama 3.1 70B

50 tok/s faster

Token Price Efficiency

DeepSeek Coder V2

$0.12/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

+10%1,365

EloHigh is better

1,240

Code Elo

High is better

1,442

Code EloHigh is better

—

LiveBench

High is better

+25%58.6%

LiveBenchHigh is better

46.8%

SWE-bench

High is better

+50%60.5%

SWE-benchHigh is better

40.2%

GPQA

High is better

+46%70.2%

GPQAHigh is better

48%

TTFT

Low is better

290 ms

TTFTLow is better

170 ms+71%

Speed

High is better

75 tok/s

SpeedHigh is better

125 tok/s+67%

In $

Low is better

+186%$0.14 / 1M

In $Low is better

$0.40 / 1M

Out $

Low is better

+43%$0.28 / 1M

Out $Low is better

$0.40 / 1M

Context

High is better

128k

ContextHigh is better

131k+2%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 54% with DeepSeek Coder V2

Monthly Volume50M tokens/mo

Quick Presets:

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

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

DeepSeek Coder V2$9.10 / mo

In: $4.9Out: $4.2

Llama 3.1 70B$20.00 / mo

In: $14Out: $6

Estimated Cost Delta

DeepSeek Coder V2 is estimated to save $10.90/month ($131/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
DeepSeek Coder V2:Pick DeepSeek Coder V2 when repo-level coding accuracy is the constraint.
2
Llama 3.1 70B:Pick Llama 3.1 70B when time-to-first-token matters more than peak Elo.
3
DeepSeek Coder V2:Pick DeepSeek Coder V2 as the default general assistant.

Recommended Workload Routing

Repo / coding agentsDeepSeek Coder V2

Higher SWE-bench (60.5%).

High-volume chatDeepSeek Coder V2

Lower output list price ($0.28/1M).

Voice / low-latency UILlama 3.1 70B

Lower TTFT (170 ms).

Long-document RAGLlama 3.1 70B

Larger window (131k).

Screenshots / visionDeepSeek Coder V2

DeepSeek Coder V2 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	DeepSeek Coder V2	Higher SWE-bench (60.5%).
High-volume chat	DeepSeek Coder V2	Lower output list price ($0.28/1M).
Voice / low-latency UI	Llama 3.1 70B	Lower TTFT (170 ms).
Long-document RAG	Llama 3.1 70B	Larger window (131k).
Screenshots / vision	DeepSeek Coder V2	DeepSeek Coder V2 is the side marked multimodal in the catalog.

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LIVE

DeepSeek

DeepSeek Coder V2

Elo 1,365

LiveBench58.6%

SWE-bench60.5%

Speed75 tok/s

Output cost$0.28/1M

Llama 3.1 70B

Elo 1,240

LiveBench46.8%

SWE-bench40.2%

Speed125 tok/s

Output cost$0.4/1M

Frequently Asked Questions

Which is better overall, DeepSeek Coder V2 or Llama 3.1 70B?: DeepSeek Coder V2 has the higher preference Elo in our latest snapshot (1,365). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, DeepSeek Coder V2 or Llama 3.1 70B?: DeepSeek Coder V2 leads SWE-bench at 60.5% vs 40.2%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: DeepSeek Coder V2 output tokens are $0.28/1M versus $0.4/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek Coder V2 or Llama 3.1 70B?: Llama 3.1 70B has the lower time-to-first-token (170 ms vs 290 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Llama 3.1 70B accepts 131k tokens versus 128k.
Can I self-host either model?: Both DeepSeek Coder V2 and Llama 3.1 70B 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 Coder V2 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 Coder V2 matchups →|All Llama 3.1 70B matchups →

DeepSeek Coder V2 vs DeepSeek V3 (next deepseek)Llama 3.1 70B vs Llama 3.1 405B (previous llama)Llama 3.1 70B vs Llama 3.3 70B (next llama)Llama 4 Maverick vs DeepSeek Coder V2 DeepSeek V4 Flash vs DeepSeek Coder V2 DeepSeek V4 Pro vs DeepSeek Coder V2

DeepSeek Coder V2 vs Llama 3.1 70B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek Coder V2 (7)vsLlama 3.1 70B (3)

DeepSeek Coder V2: 7W (70%)Overall: DeepSeek Coder V2Llama 3.1 70B: 3W (30%)

← DeepSeek Coder V2Llama 3.1 70B →

DeepSeek Coder V2 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,365vs1,240

Coding Elo

1,442vs—

SWE-bench

60.5%vs40.2%

LiveBench

58.6%vs46.8%

GPQA Diamond

70.2%vs48%

DeepSeek Coder V2: 5WLlama 3.1 70B: 0W

Llama 3.1 70B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

75 tok/svs125 tok/s

Time to first token

290 msvs170 ms

DeepSeek Coder V2: 0WLlama 3.1 70B: 2W

DeepSeek Coder V2 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.28/1Mvs$0.4/1M

Input price

$0.14/1Mvs$0.4/1M

Context window

128kvs131k

DeepSeek Coder V2: 2WLlama 3.1 70B: 1W

Recommended Workload Routing

Repo / coding agentsDeepSeek Coder V2

Higher SWE-bench (60.5%).

High-volume chatDeepSeek Coder V2

Lower output list price ($0.28/1M).

Voice / low-latency UILlama 3.1 70B

Lower TTFT (170 ms).

Long-document RAGLlama 3.1 70B

Larger window (131k).

Screenshots / visionDeepSeek Coder V2

DeepSeek Coder V2 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	DeepSeek Coder V2	Higher SWE-bench (60.5%).
High-volume chat	DeepSeek Coder V2	Lower output list price ($0.28/1M).
Voice / low-latency UI	Llama 3.1 70B	Lower TTFT (170 ms).
Long-document RAG	Llama 3.1 70B	Larger window (131k).
Screenshots / vision	DeepSeek Coder V2	DeepSeek Coder V2 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek Coder V2 or Llama 3.1 70B?

DeepSeek Coder V2 has the higher preference Elo in our latest snapshot (1,365). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, DeepSeek Coder V2 or Llama 3.1 70B?

DeepSeek Coder V2 leads SWE-bench at 60.5% vs 40.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

DeepSeek Coder V2 output tokens are $0.28/1M versus $0.4/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek Coder V2 or Llama 3.1 70B?

Llama 3.1 70B has the lower time-to-first-token (170 ms vs 290 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Llama 3.1 70B accepts 131k tokens versus 128k.

Can I self-host either model?

Both DeepSeek Coder V2 and Llama 3.1 70B 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 Coder V2 and Llama 3.1 70B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.