Pairwise benchmark snapshot · Aug 1, 2026

Llama 3.1 70B vs Qwen 2.5 Coder 32B benchmark

Name: Llama 3.1 70B vs Qwen 2.5 Coder 32B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

In this head-to-head showdown, Qwen 2.5 Coder 32B delivers higher overall intelligence and human-preferred responses (Elo 1,425 vs 1,240), while Qwen 2.5 Coder 32B leads in SWE-bench software engineering benchmarks (65.2%), 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

Llama 3.1 70B (3)Qwen 2.5 Coder 32B (6)

Llama 3.1 70B

3 of 9 Wins

✓Time to first token✓Output speed✓Output price

Qwen 2.5 Coder 32B

6 of 9 Wins

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

Qwen 2.5 Coder 32B

Δ 185 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.

Llama 3.1 70B (3)vsQwen 2.5 Coder 32B (7)

Llama 3.1 70B: 3W (30%)Overall: Qwen 2.5 Coder 32BQwen 2.5 Coder 32B: 7W (70%)

← Llama 3.1 70BQwen 2.5 Coder 32B →

🏆Qwen 2.5 Coder 32B(5/5)

Intelligence & Reasoning

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

Benchmark

Llama 3.1 70BvsQwen 2.5 Coder 32B

Preference Elo

1,240vs1,425+185

Coding Elo

—vs1,495

SWE-bench

40.2%vs65.2%+25%

LiveBench

46.8%vs64.8%+18%

GPQA Diamond

48%vs74%+26%

Llama 3.1 70B: 0WQwen 2.5 Coder 32B: 5W

🏆Llama 3.1 70B(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark

Llama 3.1 70BvsQwen 2.5 Coder 32B

Output speed

125 tok/svs110 tok/s+15 tok/s

Time to first token

170 msvs180 ms+10 ms

Llama 3.1 70B: 2WQwen 2.5 Coder 32B: 0W

🏆Qwen 2.5 Coder 32B(2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark

Llama 3.1 70BvsQwen 2.5 Coder 32B

Output price

$0.4/1Mvs$0.72/1M+$0.32/1M

Input price

$0.35/1Mvs$0.18/1M+$0.17/1M

Context window

128kvs131k+3k

Llama 3.1 70B: 1WQwen 2.5 Coder 32B: 2W

Side-by-Side Benchmark Matrix

Preference Elo+185

Llama 3.1 70B1,240

seed-bootstrap · Aug 1, 2026

Qwen 2.5 Coder 32B1,425

seed-bootstrap · Aug 1, 2026

Coding Elo

Llama 3.1 70B—

Qwen 2.5 Coder 32B1,495

seed-bootstrap · Aug 1, 2026

LiveBench+18%

Llama 3.1 70B46.8%

seed-bootstrap · Aug 1, 2026

Qwen 2.5 Coder 32B64.8%

seed-bootstrap · Aug 1, 2026

SWE-bench+25%

Llama 3.1 70B40.2%

seed-bootstrap · Aug 1, 2026

Qwen 2.5 Coder 32B65.2%

seed-bootstrap · Aug 1, 2026

GPQA Diamond+26%

Llama 3.1 70B48%

seed-bootstrap · Aug 1, 2026

Qwen 2.5 Coder 32B74%

seed-bootstrap · Aug 1, 2026

Time to first token+10 ms

Llama 3.1 70B170 ms

seed-bootstrap · Aug 1, 2026

Qwen 2.5 Coder 32B180 ms

seed-bootstrap · Aug 1, 2026

Output speed+15 tok/s

Llama 3.1 70B125 tok/s

seed-bootstrap · Aug 1, 2026

Qwen 2.5 Coder 32B110 tok/s

seed-bootstrap · Aug 1, 2026

Input price+$0.17/1M

Llama 3.1 70B$0.35/1M

seed-bootstrap · Aug 1, 2026

Qwen 2.5 Coder 32B$0.18/1M

seed-bootstrap · Aug 1, 2026

Output price+$0.32/1M

Llama 3.1 70B$0.4/1M

seed-bootstrap · Aug 1, 2026

Qwen 2.5 Coder 32B$0.72/1M

seed-bootstrap · Aug 1, 2026

Context window+3k

Llama 3.1 70B128k

seed-bootstrap · Aug 1, 2026

Qwen 2.5 Coder 32B131k

seed-bootstrap · Aug 1, 2026

Benchmark	Llama 3.1 70B	Qwen 2.5 Coder 32B	Advantage Delta
Preference Elo	1,240 seed-bootstrap · Aug 1, 2026	1,425 seed-bootstrap · Aug 1, 2026	+185
Coding Elo	—	1,495 seed-bootstrap · Aug 1, 2026	—
LiveBench	46.8% seed-bootstrap · Aug 1, 2026	64.8% seed-bootstrap · Aug 1, 2026	+18%
SWE-bench	40.2% seed-bootstrap · Aug 1, 2026	65.2% seed-bootstrap · Aug 1, 2026	+25%
GPQA Diamond	48% seed-bootstrap · Aug 1, 2026	74% seed-bootstrap · Aug 1, 2026	+26%
Time to first token	170 ms seed-bootstrap · Aug 1, 2026	180 ms seed-bootstrap · Aug 1, 2026	+10 ms
Output speed	125 tok/s seed-bootstrap · Aug 1, 2026	110 tok/s seed-bootstrap · Aug 1, 2026	+15 tok/s
Input price	$0.35/1M seed-bootstrap · Aug 1, 2026	$0.18/1M seed-bootstrap · Aug 1, 2026	+$0.17/1M
Output price	$0.4/1M seed-bootstrap · Aug 1, 2026	$0.72/1M seed-bootstrap · Aug 1, 2026	+$0.32/1M
Context window	128k seed-bootstrap · Aug 1, 2026	131k seed-bootstrap · Aug 1, 2026	+3k

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 6% with Qwen 2.5 Coder 32B

Monthly Volume50M tokens/mo

Quick Presets:

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

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

Llama 3.1 70B$18.25 / mo

In: $12.25Out: $6

Qwen 2.5 Coder 32B$17.10 / mo

In: $6.3Out: $10.8

Estimated Cost Delta

Qwen 2.5 Coder 32B is estimated to save $1.15/month ($14/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Qwen 2.5 Coder 32B:Pick Qwen 2.5 Coder 32B 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 agentsQwen 2.5 Coder 32B

Higher SWE-bench (65.2%).

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 RAGQwen 2.5 Coder 32B

Larger window (131k).

Screenshots / visionQwen 2.5 Coder 32B

Qwen 2.5 Coder 32B is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Qwen 2.5 Coder 32B	Higher SWE-bench (65.2%).
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	Qwen 2.5 Coder 32B	Larger window (131k).
Screenshots / vision	Qwen 2.5 Coder 32B	Qwen 2.5 Coder 32B is the side marked multimodal in the catalog.

Community Sentiment

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK

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

Alibaba

Qwen 2.5 Coder 32B

Elo 1,425

SWE-bench65.2%

Speed (tok/s)110 tok/s

Input / 1M Tokens$0.18/1M

Output / 1M Tokens$0.72/1M

Frequently Asked Questions

Which is better overall, Llama 3.1 70B or Qwen 2.5 Coder 32B?: Qwen 2.5 Coder 32B has the higher preference Elo in our latest snapshot (1,425). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Llama 3.1 70B or Qwen 2.5 Coder 32B?: Qwen 2.5 Coder 32B leads SWE-bench at 65.2% 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 $0.72/1M. Input prices and retry rates still move the real bill.
Which is faster, Llama 3.1 70B or Qwen 2.5 Coder 32B?: Llama 3.1 70B has the lower time-to-first-token (170 ms vs 180 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Qwen 2.5 Coder 32B accepts 131k tokens versus 128k.
Can I self-host either model?: Both Llama 3.1 70B and Qwen 2.5 Coder 32B 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. Llama 3.1 70B and Qwen 2.5 Coder 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Llama 3.1 70B matchups →|All Qwen 2.5 Coder 32B matchups →

Llama 3.1 70B vs Llama 3.1 405B (previous llama)Llama 3.1 70B vs Llama 3.3 70B (next llama)Qwen 2.5 Coder 32B vs Qwen 2.5 Plus (previous qwen)Qwen 2.5 Coder 32B vs Qwen3 235B (next qwen)Llama 4 Maverick vs Qwen 2.5 Coder 32B Qwen QwQ 32B vs Qwen 2.5 Coder 32B

Llama 3.1 70B vs Qwen 2.5 Coder 32B 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

Llama 3.1 70B

Qwen 2.5 Coder 32B

Advantage Delta

Preference Elo

1,240

seed-bootstrap · Aug 1, 2026

1,425

seed-bootstrap · Aug 1, 2026

+185

Coding Elo

—

1,495

seed-bootstrap · Aug 1, 2026

—

LiveBench

46.8%

seed-bootstrap · Aug 1, 2026

64.8%

seed-bootstrap · Aug 1, 2026

+18%

SWE-bench

40.2%

seed-bootstrap · Aug 1, 2026

65.2%

seed-bootstrap · Aug 1, 2026

+25%

GPQA Diamond

48%

seed-bootstrap · Aug 1, 2026

74%

seed-bootstrap · Aug 1, 2026

+26%

Time to first token

170 ms

seed-bootstrap · Aug 1, 2026

180 ms

seed-bootstrap · Aug 1, 2026

+10 ms

Output speed

125 tok/s

seed-bootstrap · Aug 1, 2026

110 tok/s

seed-bootstrap · Aug 1, 2026

+15 tok/s

Input price

$0.35/1M

seed-bootstrap · Aug 1, 2026

$0.18/1M

seed-bootstrap · Aug 1, 2026

+$0.17/1M

Output price

$0.4/1M

seed-bootstrap · Aug 1, 2026

$0.72/1M

seed-bootstrap · Aug 1, 2026

+$0.32/1M

Context window

128k

seed-bootstrap · Aug 1, 2026

131k

seed-bootstrap · Aug 1, 2026

+3k

Recommended Workload Routing

Repo / coding agentsQwen 2.5 Coder 32B

Higher SWE-bench (65.2%).

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 RAGQwen 2.5 Coder 32B

Larger window (131k).

Screenshots / visionQwen 2.5 Coder 32B

Qwen 2.5 Coder 32B is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Qwen 2.5 Coder 32B	Higher SWE-bench (65.2%).
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	Qwen 2.5 Coder 32B	Larger window (131k).
Screenshots / vision	Qwen 2.5 Coder 32B	Qwen 2.5 Coder 32B is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Llama 3.1 70B or Qwen 2.5 Coder 32B?

Qwen 2.5 Coder 32B has the higher preference Elo in our latest snapshot (1,425). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Llama 3.1 70B or Qwen 2.5 Coder 32B?

Qwen 2.5 Coder 32B leads SWE-bench at 65.2% 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 $0.72/1M. Input prices and retry rates still move the real bill.

Which is faster, Llama 3.1 70B or Qwen 2.5 Coder 32B?

Llama 3.1 70B has the lower time-to-first-token (170 ms vs 180 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Qwen 2.5 Coder 32B accepts 131k tokens versus 128k.

Can I self-host either model?

Both Llama 3.1 70B and Qwen 2.5 Coder 32B 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. Llama 3.1 70B and Qwen 2.5 Coder 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.