Pairwise benchmark snapshot · Aug 17, 2026

Llama 3.1 70B vs Qwen2.5 Coder 32B Instruct benchmark

Name: Llama 3.1 70B vs Qwen2.5 Coder 32B Instruct AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

In this head-to-head showdown, Qwen2.5 Coder 32B Instruct delivers higher overall intelligence and human-preferred responses (Elo 1,425 vs 1,240), while Qwen2.5 Coder 32B Instruct 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.

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Executive Verdict Summary

Llama 3.1 70B holds empirical advantage (3 of 6 metrics)

Coding / SWESWE-bench

Qwen2.5 Coder 32B InstructTop code solve rate

ReasoningGPQA / Live

Qwen2.5 Coder 32B InstructTop logical accuracy

Best Value$/1M Tok

Llama 3.1 70BLowest API billing cost

Speed / TokTok/Sec

Llama 3.1 70BFastest stream rate

Verified Advantage Breakdown

6 benchmarks evaluated across capability, speed, and cost

Llama 3.1 70B (3)Qwen2.5 Coder 32B Instruct (3)

Llama 3.1 70B

3 of 6 Wins

✓Input price✓Output price✓Context window

Qwen2.5 Coder 32B Instruct

3 of 6 Wins

✓Preference Elo✓LiveBench✓SWE-bench

Qwen2.5 Coder 32B Instruct

Δ 185 Arena Elo pts

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 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.

Llama 3.1 70B (6)vsQwen2.5 Coder 32B Instruct (4)

Llama 3.1 70B: 6W (60%)Qwen2.5 Coder 32B Instruct: 4W (40%)

← Llama 3.1 70BQwen2.5 Coder 32B Instruct →

🏆Qwen2.5 Coder 32B Instruct Leads(4/5)

Intelligence & Reasoning

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

Benchmark

Llama 3.1 70BvsQwen2.5 Coder 32B Instruct

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%vs—

Llama 3.1 70B: 1WQwen2.5 Coder 32B Instruct: 4W

🏆Llama 3.1 70B Leads(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark

Llama 3.1 70BvsQwen2.5 Coder 32B Instruct

Output speed

125 tok/svs—

Time to first token

170 msvs—

Llama 3.1 70B: 2WQwen2.5 Coder 32B Instruct: 0W

🏆Llama 3.1 70B Leads(3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark

Llama 3.1 70BvsQwen2.5 Coder 32B Instruct

Output price

$0.4/1Mvs$1/1M+$0.6/1M

Input price

$0.4/1Mvs$0.66/1M+$0.26/1M

Context window

131kvs33k+98k

Llama 3.1 70B: 3WQwen2.5 Coder 32B Instruct: 0W

Side-by-Side Benchmark Matrix

Llama 3.1 70BQwen2.5 Coder 32B Instruct

Preference EloQwen2.5 Coder 32B Instruct +185

Llama 3.1 70B1,240

Qwen2.5 Coder 32B Instruct1,425

Coding Elo

Llama 3.1 70B—

Qwen2.5 Coder 32B Instruct1,495

LiveBenchQwen2.5 Coder 32B Instruct +18%

Llama 3.1 70B46.8%

Qwen2.5 Coder 32B Instruct64.8%

SWE-benchQwen2.5 Coder 32B Instruct +25%

Llama 3.1 70B40.2%

Qwen2.5 Coder 32B Instruct65.2%

GPQA Diamond

Llama 3.1 70B48%

Qwen2.5 Coder 32B Instruct—

Time to first token

Llama 3.1 70B170 ms

Qwen2.5 Coder 32B Instruct—

Output speed

Llama 3.1 70B125 tok/s

Qwen2.5 Coder 32B Instruct—

Input priceLlama 3.1 70B +$0.26/1M

Llama 3.1 70B$0.4/1M

Qwen2.5 Coder 32B Instruct$0.66/1M

Output priceLlama 3.1 70B +$0.6/1M

Llama 3.1 70B$0.4/1M

Qwen2.5 Coder 32B Instruct$1/1M

Context windowLlama 3.1 70B +98k

Llama 3.1 70B131k

Qwen2.5 Coder 32B Instruct33k

Benchmark	Llama 3.1 70B	Qwen2.5 Coder 32B Instruct	Advantage Delta
Preference Elo	1,240 lmarena · Aug 17, 2026	1,425 lmarena · Aug 17, 2026	+185
Coding Elo	—	1,495 lmarena · Aug 17, 2026	—
LiveBench	46.8% livebench · Aug 17, 2026	64.8% livebench · Aug 17, 2026	+18%
SWE-bench	40.2% swebench · Aug 17, 2026	65.2% swebench · Aug 17, 2026	+25%
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	$0.4/1M openrouter · Aug 17, 2026	$0.66/1M openrouter · Aug 17, 2026	+$0.26/1M
Output price	$0.4/1M openrouter · Aug 17, 2026	$1/1M openrouter · Aug 17, 2026	+$0.6/1M
Context window	131k openrouter · Aug 17, 2026	33k openrouter · Aug 17, 2026	+98k

Workload Cost & Savings Calculator

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

Save 48% 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)

Llama 3.1 70B$20.00 / mo

In: $14Out: $6

Qwen2.5 Coder 32B Instruct$38.10 / mo

In: $23.1Out: $15

Estimated Cost Delta

Llama 3.1 70B is estimated to save $18.10/month ($217/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Qwen2.5 Coder 32B Instruct:Pick Qwen2.5 Coder 32B Instruct 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
Qwen2.5 Coder 32B Instruct:Pick Qwen2.5 Coder 32B Instruct as the default general assistant.

Recommended Workload Routing

Repo / coding agentsQwen2.5 Coder 32B Instruct

Higher SWE-bench (65.2%).

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 RAGLlama 3.1 70B

Larger window (131k).

Screenshots / visionQwen2.5 Coder 32B Instruct

Qwen2.5 Coder 32B Instruct is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Qwen2.5 Coder 32B Instruct	Higher SWE-bench (65.2%).
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	Llama 3.1 70B	Larger window (131k).
Screenshots / vision	Qwen2.5 Coder 32B Instruct	Qwen2.5 Coder 32B Instruct is the side marked multimodal in the catalog.

Cast Your Matchup Vote

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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$0.4/1M

Output / 1M Tokens$0.4/1M

Alibaba

Qwen2.5 Coder 32B Instruct

Elo 1,425

SWE-bench65.2%

Speed (tok/s)33k

Input / 1M Tokens$0.66/1M

Output / 1M Tokens$1/1M

Frequently Asked Questions

Which is better overall, Llama 3.1 70B or Qwen2.5 Coder 32B Instruct?: Qwen2.5 Coder 32B Instruct 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 Qwen2.5 Coder 32B Instruct?: Qwen2.5 Coder 32B Instruct 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 $1/1M. Input prices and retry rates still move the real bill.
Which is faster, Llama 3.1 70B or Qwen2.5 Coder 32B Instruct?: We do not have TTFT for both models.
Which has the larger context window?: Llama 3.1 70B accepts 131k tokens versus 33k.
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. Llama 3.1 70B and Qwen2.5 Coder 32B Instruct 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 Qwen2.5 Coder 32B Instruct matchups →

Llama 3.1 70B vs Llama 3.1 405B (previous llama)Llama 3.1 70B vs Llama 3.3 70B (next llama)Qwen2.5 Coder 32B Instruct vs Qwen 2.5 Plus (next qwen)Qwen 3 Max vs Qwen2.5 Coder 32B Instruct Llama 4 Maverick vs Qwen2.5 Coder 32B Instruct Qwen QwQ 32B vs Qwen2.5 Coder 32B Instruct

Llama 3.1 70B vs Qwen2.5 Coder 32B Instruct 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

Llama 3.1 70BQwen2.5 Coder 32B Instruct

Preference EloQwen2.5 Coder 32B Instruct +185

Llama 3.1 70B1,240

Qwen2.5 Coder 32B Instruct1,425

Coding Elo

Llama 3.1 70B—

Qwen2.5 Coder 32B Instruct1,495

LiveBenchQwen2.5 Coder 32B Instruct +18%

Llama 3.1 70B46.8%

Qwen2.5 Coder 32B Instruct64.8%

SWE-benchQwen2.5 Coder 32B Instruct +25%

Llama 3.1 70B40.2%

Qwen2.5 Coder 32B Instruct65.2%

GPQA Diamond

Llama 3.1 70B48%

Qwen2.5 Coder 32B Instruct—

Time to first token

Llama 3.1 70B170 ms

Qwen2.5 Coder 32B Instruct—

Output speed

Llama 3.1 70B125 tok/s

Qwen2.5 Coder 32B Instruct—

Input priceLlama 3.1 70B +$0.26/1M

Llama 3.1 70B$0.4/1M

Qwen2.5 Coder 32B Instruct$0.66/1M

Output priceLlama 3.1 70B +$0.6/1M

Llama 3.1 70B$0.4/1M

Qwen2.5 Coder 32B Instruct$1/1M

Context windowLlama 3.1 70B +98k

Llama 3.1 70B131k

Qwen2.5 Coder 32B Instruct33k

Benchmark

Llama 3.1 70B

Qwen2.5 Coder 32B Instruct

Advantage Delta

Preference Elo

1,240

lmarena · Aug 17, 2026

1,425

lmarena · Aug 17, 2026

+185

Coding Elo

—

1,495

lmarena · Aug 17, 2026

—

LiveBench

46.8%

livebench · Aug 17, 2026

64.8%

livebench · Aug 17, 2026

+18%

SWE-bench

40.2%

swebench · Aug 17, 2026

65.2%

swebench · Aug 17, 2026

+25%

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

$0.4/1M

openrouter · Aug 17, 2026

$0.66/1M

openrouter · Aug 17, 2026

+$0.26/1M

Output price

$0.4/1M

openrouter · Aug 17, 2026

$1/1M

openrouter · Aug 17, 2026

+$0.6/1M

Context window

131k

openrouter · Aug 17, 2026

33k

openrouter · Aug 17, 2026

+98k

Recommended Workload Routing

Repo / coding agentsQwen2.5 Coder 32B Instruct

Higher SWE-bench (65.2%).

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 RAGLlama 3.1 70B

Larger window (131k).

Screenshots / visionQwen2.5 Coder 32B Instruct

Qwen2.5 Coder 32B Instruct is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Qwen2.5 Coder 32B Instruct	Higher SWE-bench (65.2%).
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	Llama 3.1 70B	Larger window (131k).
Screenshots / vision	Qwen2.5 Coder 32B Instruct	Qwen2.5 Coder 32B Instruct is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Llama 3.1 70B or Qwen2.5 Coder 32B Instruct?

Qwen2.5 Coder 32B Instruct 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 Qwen2.5 Coder 32B Instruct?

Qwen2.5 Coder 32B Instruct 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 $1/1M. Input prices and retry rates still move the real bill.

Which is faster, Llama 3.1 70B or Qwen2.5 Coder 32B Instruct?

We do not have TTFT for both models.

Which has the larger context window?

Llama 3.1 70B accepts 131k tokens versus 33k.

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. Llama 3.1 70B and Qwen2.5 Coder 32B Instruct Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.