Pairwise benchmark snapshot · Aug 1, 2026

Claude 3.5 Sonnet vs Llama 3.1 70B benchmark

Name: Claude 3.5 Sonnet vs Llama 3.1 70B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

In this head-to-head showdown, Claude 3.5 Sonnet delivers higher overall intelligence and human-preferred responses (Elo 1,280 vs 1,240), while Claude 3.5 Sonnet leads in SWE-bench software engineering benchmarks (49%), while 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

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

Claude 3.5 Sonnet (5)Llama 3.1 70B (4)

Claude 3.5 Sonnet

5 of 9 Wins

✓Preference Elo✓LiveBench✓SWE-bench✓GPQA Diamond✓Context window

Llama 3.1 70B

4 of 9 Wins

✓Time to first token✓Output speed✓Input price✓Output price

Anthropic

Leads 5 of 9 metrics

Claude 3.5 Sonnet

2024 workhorse. Still a high-intent compare against GPT-4o.

Elo 1,280$15/1M out

Claude 3.5 Sonnet

Δ 40 Arena Elo pts

Throughput LeaderLlama 3.1 70B Wins

Llama 3.1 70B

125 tok/s

Value per Dollar LeaderLlama 3.1 70B Wins

Llama 3.1 70B

$0.4 / 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

Percentile 0–100

Head-to-Head Comparison

Overall Matchup Breakdown

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

Claude 3.5 Sonnet (5)vsLlama 3.1 70B (4)

Claude 3.5 Sonnet: 5W (56%)Overall: Claude 3.5 SonnetLlama 3.1 70B: 4W (44%)

← Claude 3.5 SonnetLlama 3.1 70B →

🏆Claude 3.5 Sonnet(4/5)

Intelligence & Reasoning

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

Benchmark

Claude 3.5 SonnetvsLlama 3.1 70B

Preference Elo

1,280vs1,240+40

Coding Elo

—vs—

SWE-bench

49%vs40.2%+8.8%

LiveBench

52.1%vs46.8%+5.3%

GPQA Diamond

65%vs48%+17%

Claude 3.5 Sonnet: 4WLlama 3.1 70B: 0W

🏆Llama 3.1 70B(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark

Claude 3.5 SonnetvsLlama 3.1 70B

Output speed

80 tok/svs125 tok/s+45 tok/s

Time to first token

280 msvs170 ms+110 ms

Claude 3.5 Sonnet: 0WLlama 3.1 70B: 2W

🏆Llama 3.1 70B(2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark

Claude 3.5 SonnetvsLlama 3.1 70B

Output price

$15/1Mvs$0.4/1M+$14.6/1M

Input price

$3/1Mvs$0.35/1M+$2.65/1M

Context window

200kvs128k+72k

Claude 3.5 Sonnet: 1WLlama 3.1 70B: 2W

Side-by-Side Benchmark Matrix

Preference Elo+40

Claude 3.5 Sonnet1,280

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B1,240

seed-bootstrap · Aug 1, 2026

LiveBench+5.3%

Claude 3.5 Sonnet52.1%

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B46.8%

seed-bootstrap · Aug 1, 2026

SWE-bench+8.8%

Claude 3.5 Sonnet49%

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B40.2%

seed-bootstrap · Aug 1, 2026

GPQA Diamond+17%

Claude 3.5 Sonnet65%

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B48%

seed-bootstrap · Aug 1, 2026

Time to first token+110 ms

Claude 3.5 Sonnet280 ms

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B170 ms

seed-bootstrap · Aug 1, 2026

Output speed+45 tok/s

Claude 3.5 Sonnet80 tok/s

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B125 tok/s

seed-bootstrap · Aug 1, 2026

Input price+$2.65/1M

Claude 3.5 Sonnet$3/1M

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B$0.35/1M

seed-bootstrap · Aug 1, 2026

Output price+$14.6/1M

Claude 3.5 Sonnet$15/1M

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B$0.4/1M

seed-bootstrap · Aug 1, 2026

Context window+72k

Claude 3.5 Sonnet200k

seed-bootstrap · Aug 1, 2026

Llama 3.1 70B128k

seed-bootstrap · Aug 1, 2026

Benchmark	Claude 3.5 Sonnet	Llama 3.1 70B	Advantage Delta
Preference Elo	1,280 seed-bootstrap · Aug 1, 2026	1,240 seed-bootstrap · Aug 1, 2026	+40
LiveBench	52.1% seed-bootstrap · Aug 1, 2026	46.8% seed-bootstrap · Aug 1, 2026	+5.3%
SWE-bench	49% seed-bootstrap · Aug 1, 2026	40.2% seed-bootstrap · Aug 1, 2026	+8.8%
GPQA Diamond	65% seed-bootstrap · Aug 1, 2026	48% seed-bootstrap · Aug 1, 2026	+17%
Time to first token	280 ms seed-bootstrap · Aug 1, 2026	170 ms seed-bootstrap · Aug 1, 2026	+110 ms
Output speed	80 tok/s seed-bootstrap · Aug 1, 2026	125 tok/s seed-bootstrap · Aug 1, 2026	+45 tok/s
Input price	$3/1M seed-bootstrap · Aug 1, 2026	$0.35/1M seed-bootstrap · Aug 1, 2026	+$2.65/1M
Output price	$15/1M seed-bootstrap · Aug 1, 2026	$0.4/1M seed-bootstrap · Aug 1, 2026	+$14.6/1M
Context window	200k seed-bootstrap · Aug 1, 2026	128k seed-bootstrap · Aug 1, 2026	+72k

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 94% 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)

Claude 3.5 Sonnet$330.00 / mo

In: $105Out: $225

Llama 3.1 70B$18.25 / mo

In: $12.25Out: $6

Estimated Cost Delta

Llama 3.1 70B is estimated to save $311.75/month ($3,741/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Claude 3.5 Sonnet:Pick Claude 3.5 Sonnet when repo-level coding accuracy is the constraint.
2
Llama 3.1 70B:Pick Llama 3.1 70B when you are optimizing output cost.
3
Llama 3.1 70B:Pick Llama 3.1 70B when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsClaude 3.5 Sonnet

Higher SWE-bench (49%).

High-volume chatLlama 3.1 70B

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

Voice / low-latency UILlama 3.1 70B

Lower TTFT (170 ms).

Long-document RAGClaude 3.5 Sonnet

Larger window (200k).

Screenshots / visionClaude 3.5 Sonnet

Claude 3.5 Sonnet is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Claude 3.5 Sonnet	Higher SWE-bench (49%).
High-volume chat	Llama 3.1 70B	Lower output list price ($0.4/1M).
Voice / low-latency UI	Llama 3.1 70B	Lower TTFT (170 ms).
Long-document RAG	Claude 3.5 Sonnet	Larger window (200k).
Screenshots / vision	Claude 3.5 Sonnet	Claude 3.5 Sonnet is the side marked multimodal in the catalog.

Community Sentiment

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK

Anthropic

Claude 3.5 Sonnet

Elo 1,280

SWE-bench49%

Speed (tok/s)80 tok/s

Input / 1M Tokens$3/1M

Output / 1M Tokens$15/1M

Llama 3.1 70B

Elo 1,240

SWE-bench40.2%

Speed (tok/s)125 tok/s

Input / 1M Tokens$0.35/1M

Output / 1M Tokens$0.4/1M

Frequently Asked Questions

Which is better overall, Claude 3.5 Sonnet or Llama 3.1 70B?: Claude 3.5 Sonnet has the higher preference Elo in our latest snapshot (1,280). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Claude 3.5 Sonnet or Llama 3.1 70B?: Claude 3.5 Sonnet leads SWE-bench at 49% vs 40.2%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Llama 3.1 70B output tokens are $0.4/1M versus $15/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude 3.5 Sonnet or Llama 3.1 70B?: Llama 3.1 70B has the lower time-to-first-token (170 ms vs 280 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Claude 3.5 Sonnet accepts 200k tokens versus 128k.
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. Claude 3.5 Sonnet 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 Claude 3.5 Sonnet matchups →|All Llama 3.1 70B matchups →

Claude 3.5 Sonnet vs Claude 3.7 Sonnet (next sonnet)Llama 3.1 70B vs Llama 3.1 405B (previous llama)Llama 3.1 70B vs Llama 3.3 70B (next llama)Claude Opus 4.5 vs Claude 3.5 Sonnet Claude Opus 4.6 vs Claude 3.5 Sonnet Claude Sonnet 4.5 vs Claude 3.5 Sonnet

Claude 3.5 Sonnet vs Llama 3.1 70B 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 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

Percentile 0–100

Benchmark

Claude 3.5 Sonnet

Llama 3.1 70B

Advantage Delta

Preference Elo

1,280

seed-bootstrap · Aug 1, 2026

1,240

seed-bootstrap · Aug 1, 2026

+40

LiveBench

52.1%

seed-bootstrap · Aug 1, 2026

46.8%

seed-bootstrap · Aug 1, 2026

+5.3%

SWE-bench

49%

seed-bootstrap · Aug 1, 2026

40.2%

seed-bootstrap · Aug 1, 2026

+8.8%

GPQA Diamond

65%

seed-bootstrap · Aug 1, 2026

48%

seed-bootstrap · Aug 1, 2026

+17%

Time to first token

280 ms

seed-bootstrap · Aug 1, 2026

170 ms

seed-bootstrap · Aug 1, 2026

+110 ms

Output speed

80 tok/s

seed-bootstrap · Aug 1, 2026

125 tok/s

seed-bootstrap · Aug 1, 2026

+45 tok/s

Input price

$3/1M

seed-bootstrap · Aug 1, 2026

$0.35/1M

seed-bootstrap · Aug 1, 2026

+$2.65/1M

Output price

$15/1M

seed-bootstrap · Aug 1, 2026

$0.4/1M

seed-bootstrap · Aug 1, 2026

+$14.6/1M

Context window

200k

seed-bootstrap · Aug 1, 2026

128k

seed-bootstrap · Aug 1, 2026

+72k

Recommended Workload Routing

Repo / coding agentsClaude 3.5 Sonnet

Higher SWE-bench (49%).

High-volume chatLlama 3.1 70B

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

Voice / low-latency UILlama 3.1 70B

Lower TTFT (170 ms).

Long-document RAGClaude 3.5 Sonnet

Larger window (200k).

Screenshots / visionClaude 3.5 Sonnet

Claude 3.5 Sonnet is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Claude 3.5 Sonnet	Higher SWE-bench (49%).
High-volume chat	Llama 3.1 70B	Lower output list price ($0.4/1M).
Voice / low-latency UI	Llama 3.1 70B	Lower TTFT (170 ms).
Long-document RAG	Claude 3.5 Sonnet	Larger window (200k).
Screenshots / vision	Claude 3.5 Sonnet	Claude 3.5 Sonnet is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Claude 3.5 Sonnet or Llama 3.1 70B?

Claude 3.5 Sonnet has the higher preference Elo in our latest snapshot (1,280). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Claude 3.5 Sonnet or Llama 3.1 70B?

Claude 3.5 Sonnet leads SWE-bench at 49% vs 40.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Llama 3.1 70B output tokens are $0.4/1M versus $15/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude 3.5 Sonnet or Llama 3.1 70B?

Llama 3.1 70B has the lower time-to-first-token (170 ms vs 280 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Claude 3.5 Sonnet accepts 200k tokens versus 128k.

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. Claude 3.5 Sonnet and Llama 3.1 70B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.