Pairwise benchmark snapshot · Aug 16, 2026noindex (thin pair)

DeepSeek V3 vs Qwen2.5 Coder 32B Instruct benchmark

Name: DeepSeek V3 vs Qwen2.5 Coder 32B Instruct AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek V3 (DeepSeek) and Qwen2.5 Coder 32B Instruct (Alibaba) using the latest snapshots we have as of Aug 16, 2026. Qwen2.5 Coder 32B Instruct wins on output price at $1/1M. DeepSeek V3 has the larger context window (164k 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 V3

Prior DeepSeek flagship. Baseline for v3 vs v4.

Elo 1,310$1.0287/1M out

Alibaba

Qwen2.5 Coder 32B Instruct

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

$1/1M 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 V3 (8)vsQwen2.5 Coder 32B Instruct (1)

DeepSeek V3: 8W (89%)Overall: DeepSeek V3Qwen2.5 Coder 32B Instruct: 1W (11%)

← DeepSeek V3Qwen2.5 Coder 32B Instruct →

DeepSeek V3 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,310vs—

Coding Elo

—vs—

SWE-bench

48.6%vs—

LiveBench

55.4%vs—

GPQA Diamond

59.1%vs—

DeepSeek V3: 4WQwen2.5 Coder 32B Instruct: 0W

DeepSeek V3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

66 tok/svs—

Time to first token

380 msvs—

DeepSeek V3: 2WQwen2.5 Coder 32B Instruct: 0W

DeepSeek V3 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.03/1Mvs$1/1M

Input price

$0.26/1Mvs$0.66/1M

Context window

164kvs33k

DeepSeek V3: 2WQwen2.5 Coder 32B Instruct: 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 V3 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

Qwen2.5 Coder 32B Instruct

$0.03/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,310

EloHigh is better

—

LiveBench

High is better

55.4%

LiveBenchHigh is better

—

SWE-bench

High is better

48.6%

SWE-benchHigh is better

—

GPQA

High is better

59.1%

GPQAHigh is better

—

TTFT

Low is better

380 ms

TTFTLow is better

—

Speed

High is better

66 tok/s

SpeedHigh is better

—

In $

Low is better

+156%$0.26/1M

In $Low is better

$0.66/1M

Out $

Low is better

$1.03/1M

Out $Low is better

$1/1M+3%

Context

High is better

+400%164k

ContextHigh is better

33k

Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Save up to 36% with DeepSeek V3

Monthly Volume50M tokens/mo

Quick Presets:

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

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

DeepSeek V3$24.44 / mo

In: $9.01Out: $15.43

Qwen2.5 Coder 32B Instruct$38.10 / mo

In: $23.10Out: $15.00

Estimated Cost Delta

DeepSeek V3 is estimated to save $13.66/month ($164/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Qwen2.5 Coder 32B Instruct:Pick Qwen2.5 Coder 32B Instruct when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

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 V3

Larger window (164k).

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	insufficient data	Need SWE-bench on both sides.
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 V3	Larger window (164k).
Screenshots / vision	Qwen2.5 Coder 32B Instruct	Qwen2.5 Coder 32B Instruct is the side marked multimodal in the catalog.

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CompareLLM Matrix

Verified head-to-head card

LIVE

DeepSeek

DeepSeek V3

Elo 1,310

LiveBench55.4%

SWE-bench48.6%

Speed66 tok/s

Output cost$1.03/1M

Alibaba

Qwen2.5 Coder 32B Instruct

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$1/1M

Frequently Asked Questions

Which is better overall, DeepSeek V3 or Qwen2.5 Coder 32B Instruct?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, DeepSeek V3 or Qwen2.5 Coder 32B Instruct?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: Qwen2.5 Coder 32B Instruct output tokens are $1/1M versus $1.03/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek V3 or Qwen2.5 Coder 32B Instruct?: We do not have TTFT for both models.
Which has the larger context window?: DeepSeek V3 accepts 164k tokens versus 33k.
Can I self-host either model?: DeepSeek V3 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 V3 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 V3 matchups →|All Qwen2.5 Coder 32B Instruct matchups →

DeepSeek V3 vs DeepSeek Coder V2 (previous deepseek)DeepSeek V3 vs DeepSeek R1 (next deepseek)DeepSeek V4 Pro vs DeepSeek V3 Qwen 3 Max vs DeepSeek V3 Qwen QwQ 32B vs DeepSeek V3 DeepSeek V4 Flash vs DeepSeek V3

DeepSeek V3 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 V3 (8)vsQwen2.5 Coder 32B Instruct (1)

DeepSeek V3: 8W (89%)Overall: DeepSeek V3Qwen2.5 Coder 32B Instruct: 1W (11%)

← DeepSeek V3Qwen2.5 Coder 32B Instruct →

DeepSeek V3 (4/5)

Intelligence & Reasoning

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

Preference Elo

1,310vs—

Coding Elo

—vs—

SWE-bench

48.6%vs—

LiveBench

55.4%vs—

GPQA Diamond

59.1%vs—

DeepSeek V3: 4WQwen2.5 Coder 32B Instruct: 0W

DeepSeek V3 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

66 tok/svs—

Time to first token

380 msvs—

DeepSeek V3: 2WQwen2.5 Coder 32B Instruct: 0W

DeepSeek V3 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.03/1Mvs$1/1M

Input price

$0.26/1Mvs$0.66/1M

Context window

164kvs33k

DeepSeek V3: 2WQwen2.5 Coder 32B Instruct: 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

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 V3

Larger window (164k).

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	insufficient data	Need SWE-bench on both sides.
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 V3	Larger window (164k).
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 V3 or Qwen2.5 Coder 32B Instruct?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, DeepSeek V3 or Qwen2.5 Coder 32B Instruct?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

Qwen2.5 Coder 32B Instruct output tokens are $1/1M versus $1.03/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek V3 or Qwen2.5 Coder 32B Instruct?

We do not have TTFT for both models.

Which has the larger context window?

DeepSeek V3 accepts 164k tokens versus 33k.

Can I self-host either model?

DeepSeek V3 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 V3 and Qwen2.5 Coder 32B Instruct Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.