Pairwise benchmark snapshot · Aug 17, 2026

DeepSeek R1 vs Qwen2.5 Coder 32B Instruct benchmark

Name: DeepSeek R1 vs Qwen2.5 Coder 32B Instruct AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek R1 (DeepSeek) and Qwen2.5 Coder 32B Instruct (Alibaba) using the latest snapshots we have as of Aug 17, 2026. On preference Elo, Qwen2.5 Coder 32B Instruct is ahead by 67 points (1,425 vs 1,358; lmarena (Aug 17, 2026)). On SWE-bench coding, DeepSeek R1 resolves 65.2% versus 65.2% (swebench (Aug 17, 2026)). Qwen2.5 Coder 32B Instruct wins on output price at $1/1M. DeepSeek R1 has the larger context window (64k 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 R1

Open-weights reasoning model trained with large-scale RL.

Elo 1,358$2.5/1M out

Alibaba

Qwen2.5 Coder 32B Instruct

Auto-discovered from OpenRouter (qwen/qwen-2.5-coder-32b-instruct). Preview until a second source matches.

Elo 1,425$1/1M out

DeepSeek R1 Inference Compute Profile

Inference-Time Compute & Reasoning EffortDynamic CoT

DeepSeek R1 Reasoning Scaler & Token Billing Simulator

Param: enable_reasoning

Reasoning models scale test-time compute by generating hidden chain-of-thought (CoT) tokens. These tokens are billed at standard output rates and directly expand latency (TTFT) in exchange for higher GPQA Diamond and SWE-bench Verified problem resolve rates.

Estimated TTFT

420 ms

1.0x (Standard eval)

CoT Thinking Tokens

~2,800

Billed as output tokens

Est. Cost / 1k Calls

$8.10

7.4x base invoice

STEM / SWE Boost

+6.5%

GPQA & SWE-bench scaling

Medium (Full RL CoT) Operational Profile

Standard large-scale RL reasoning trace with self-correction.

Direct Provider APIDeepSeek

"enable_reasoning": true

OpenRouter Unified APIUnified Gateway

"reasoning": {
  "effort": "medium",
  "max_tokens": 2800
}

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Instant pairwise benchmark recalculation across 400+ LLMs

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 R1 (4)vsQwen2.5 Coder 32B Instruct (5)

DeepSeek R1: 4W (44%)Overall: Qwen2.5 Coder 32B InstructQwen2.5 Coder 32B Instruct: 5W (56%)

← DeepSeek R11 tiesQwen2.5 Coder 32B Instruct →

Qwen2.5 Coder 32B Instruct (3/5)

Intelligence & Reasoning

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

Preference Elo

1,358vs1,425

Coding Elo

—vs1,495

SWE-bench

65.2%vs65.2%

LiveBench

59%vs64.8%

GPQA Diamond

79.8%vs—

DeepSeek R1: 1WQwen2.5 Coder 32B Instruct: 3W

DeepSeek R1 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

62 tok/svs—

Time to first token

420 msvs—

DeepSeek R1: 2WQwen2.5 Coder 32B Instruct: 0W

Qwen2.5 Coder 32B Instruct (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.5/1Mvs$1/1M

Input price

$0.7/1Mvs$0.66/1M

Context window

64kvs33k

DeepSeek R1: 1WQwen2.5 Coder 32B Instruct: 2W

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 AdvantageEven 3–3

Preference Elo

Qwen2.5 Coder 32B Instruct

67 pts advantage

Throughput Speed

No shared data

Token Price Efficiency

Qwen2.5 Coder 32B Instruct

$1.50/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,358

EloHigh is better

1,425+5%

Code Elo

High is better

—

Code EloHigh is better

1,495

LiveBench

High is better

59%

LiveBenchHigh is better

64.8%+10%

SWE-bench

High is better

65.2%

SWE-benchHigh is better

65.2%

GPQA

High is better

79.8%

GPQAHigh is better

—

TTFT

Low is better

420 ms

TTFTLow is better

—

Speed

High is better

62 tok/s

SpeedHigh is better

—

In $

Low is better

$0.70 / 1M

In $Low is better

$0.66 / 1M+6%

Out $

Low is better

$2.50 / 1M

Out $Low is better

$1.00 / 1M+150%

Context

High is better

+95%64k

ContextHigh is better

33k

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 39% with Qwen2.5 Coder 32B Instruct

Monthly Volume50M tokens/mo

Quick Presets:

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

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

DeepSeek R1$62.00 / mo

In: $24.5Out: $37.5

Qwen2.5 Coder 32B Instruct$38.10 / mo

In: $23.1Out: $15

Estimated Cost Delta

Qwen2.5 Coder 32B Instruct is estimated to save $23.90/month ($287/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
DeepSeek R1:Pick DeepSeek R1 when repo-level coding accuracy is the constraint.
2
Qwen2.5 Coder 32B Instruct:Pick Qwen2.5 Coder 32B Instruct 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 agentsDeepSeek R1

Higher SWE-bench (65.2%).

High-volume chatQwen2.5 Coder 32B Instruct

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGDeepSeek R1

Larger window (64k).

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	DeepSeek R1	Higher SWE-bench (65.2%).
High-volume chat	Qwen2.5 Coder 32B Instruct	Lower output list price ($1/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	DeepSeek R1	Larger window (64k).
Screenshots / vision	Qwen2.5 Coder 32B Instruct	Qwen2.5 Coder 32B Instruct is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchJan 20, 2025

DeepSeek R1 stays as the open-weights RL baseline

Jan 2025 reasoning model. Still searched. V4 Pro is the newer DeepSeek buy.

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CompareLLM Matrix

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LIVE

DeepSeek

DeepSeek R1

Elo 1,358

LiveBench59%

SWE-bench65.2%

Speed62 tok/s

Output cost$2.5/1M

Alibaba

Qwen2.5 Coder 32B Instruct

Elo 1,425

LiveBench64.8%

SWE-bench65.2%

Speed—

Output cost$1/1M

Frequently Asked Questions

Which is better overall, DeepSeek R1 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, DeepSeek R1 or Qwen2.5 Coder 32B Instruct?: DeepSeek R1 leads SWE-bench at 65.2% vs 65.2%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Qwen2.5 Coder 32B Instruct output tokens are $1/1M versus $2.5/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek R1 or Qwen2.5 Coder 32B Instruct?: We do not have TTFT for both models.
Which has the larger context window?: DeepSeek R1 accepts 64k tokens versus 33k.
Can I self-host either model?: DeepSeek R1 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. DeepSeek R1 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 DeepSeek R1 matchups →|All Qwen2.5 Coder 32B Instruct matchups →

DeepSeek R1 vs DeepSeek V3 (previous deepseek)DeepSeek R1 vs DeepSeek V4 Pro (next deepseek)Qwen2.5 Coder 32B Instruct vs Qwen 2.5 Plus (next qwen)DeepSeek V4 Flash vs Qwen2.5 Coder 32B Instruct Qwen QwQ 32B vs Qwen2.5 Coder 32B Instruct DeepSeek V4 Pro vs Qwen2.5 Coder 32B Instruct

DeepSeek R1 vs Qwen2.5 Coder 32B Instruct benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek R1 (4)vsQwen2.5 Coder 32B Instruct (5)

DeepSeek R1: 4W (44%)Overall: Qwen2.5 Coder 32B InstructQwen2.5 Coder 32B Instruct: 5W (56%)

← DeepSeek R11 tiesQwen2.5 Coder 32B Instruct →

Qwen2.5 Coder 32B Instruct (3/5)

Intelligence & Reasoning

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

Preference Elo

1,358vs1,425

Coding Elo

—vs1,495

SWE-bench

65.2%vs65.2%

LiveBench

59%vs64.8%

GPQA Diamond

79.8%vs—

DeepSeek R1: 1WQwen2.5 Coder 32B Instruct: 3W

DeepSeek R1 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

62 tok/svs—

Time to first token

420 msvs—

DeepSeek R1: 2WQwen2.5 Coder 32B Instruct: 0W

Qwen2.5 Coder 32B Instruct (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.5/1Mvs$1/1M

Input price

$0.7/1Mvs$0.66/1M

Context window

64kvs33k

DeepSeek R1: 1WQwen2.5 Coder 32B Instruct: 2W

Recommended Workload Routing

Repo / coding agentsDeepSeek R1

Higher SWE-bench (65.2%).

High-volume chatQwen2.5 Coder 32B Instruct

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGDeepSeek R1

Larger window (64k).

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	DeepSeek R1	Higher SWE-bench (65.2%).
High-volume chat	Qwen2.5 Coder 32B Instruct	Lower output list price ($1/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	DeepSeek R1	Larger window (64k).
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, DeepSeek R1 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, DeepSeek R1 or Qwen2.5 Coder 32B Instruct?

DeepSeek R1 leads SWE-bench at 65.2% vs 65.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Qwen2.5 Coder 32B Instruct output tokens are $1/1M versus $2.5/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek R1 or Qwen2.5 Coder 32B Instruct?

We do not have TTFT for both models.

Which has the larger context window?

DeepSeek R1 accepts 64k tokens versus 33k.

Can I self-host either model?

DeepSeek R1 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. DeepSeek R1 and Qwen2.5 Coder 32B Instruct Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

DeepSeek R1 Reasoning Scaler & Token Billing Simulator

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

Qwen2.5 Coder 32B Instruct

No shared data

Qwen2.5 Coder 32B Instruct

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

DeepSeek R1

Qwen2.5 Coder 32B Instruct

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

DeepSeek R1 Reasoning Scaler & Token Billing Simulator

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

Qwen2.5 Coder 32B Instruct

No shared data

Qwen2.5 Coder 32B Instruct

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

DeepSeek R1

Qwen2.5 Coder 32B Instruct

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons