Pairwise benchmark snapshot · Aug 1, 2026

DeepSeek Coder V2 vs Yi-Lightning benchmark

Name: DeepSeek Coder V2 vs Yi-Lightning AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek Coder V2 (DeepSeek) and Yi-Lightning (01.AI) using the latest snapshots we have as of Aug 1, 2026. On preference Elo, Yi-Lightning is ahead by 110 points (1,475 vs 1,365; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, Yi-Lightning resolves 63.4% versus 60.5% (seed-bootstrap (Aug 1, 2026)). Yi-Lightning streams faster (130 tok/s) while Yi-Lightning is the cheaper output token ($0.14/1M). DeepSeek Coder V2 has the larger context window (128k 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 Coder V2

DeepSeek open-weight Mixture-of-Experts coding model supporting 338 programming languages and 128k context.

Elo 1,365$0.28/1M out

01.AI

Yi-Lightning

01.AI ultra-fast reasoning model delivering top LiveBench efficiency.

Elo 1,475$0.14/1M 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 Coder V2 (1)vsYi-Lightning (8)

DeepSeek Coder V2: 1W (11%)Overall: Yi-LightningYi-Lightning: 8W (89%)

← DeepSeek Coder V21 tiesYi-Lightning →

Yi-Lightning (5/5)

Intelligence & Reasoning

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

Preference Elo

1,365vs1,475

Coding Elo

1,442vs1,480

SWE-bench

60.5%vs63.4%

LiveBench

58.6%vs65%

GPQA Diamond

70.2%vs78%

DeepSeek Coder V2: 0WYi-Lightning: 5W

Yi-Lightning (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

75 tok/svs130 tok/s

Time to first token

290 msvs150 ms

DeepSeek Coder V2: 0WYi-Lightning: 2W

Tied (1/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.28/1Mvs$0.14/1M

Input price

$0.14/1Mvs$0.14/1M

Context window

128kvs16k

DeepSeek Coder V2: 1WYi-Lightning: 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 AdvantageYi-Lightning 5/6

Preference Elo

Yi-Lightning

110 pts advantage

Throughput Speed

Yi-Lightning

55 tok/s faster

Price Efficiency

Yi-Lightning

$0.14/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,365

EloHigh is better

1,475+8%

Code Elo

High is better

1,442

Code EloHigh is better

1,480+3%

LiveBench

High is better

58.6%

LiveBenchHigh is better

65%+11%

SWE-bench

High is better

60.5%

SWE-benchHigh is better

63.4%+5%

GPQA

High is better

70.2%

GPQAHigh is better

78%+11%

TTFT

Low is better

290 ms

TTFTLow is better

150 ms+93%

Speed

High is better

75 tok/s

SpeedHigh is better

130 tok/s+73%

In $

Low is better

$0.14/1M

In $Low is better

$0.14/1M

Out $

Low is better

$0.28/1M

Out $Low is better

$0.14/1M+100%

Context

High is better

+681%128k

ContextHigh is better

16k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 23% with Yi-Lightning

Monthly Volume50M tokens/mo

Quick Presets:

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

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

DeepSeek Coder V2$9.10 / mo

In: $4.90Out: $4.20

Yi-Lightning$7.00 / mo

In: $4.90Out: $2.10

Estimated Cost Delta

Yi-Lightning is estimated to save $2.10/month ($25/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Yi-Lightning:Pick Yi-Lightning when repo-level coding accuracy is the constraint.
2
Yi-Lightning:Pick Yi-Lightning when time-to-first-token matters more than peak Elo.
3
Yi-Lightning:Pick Yi-Lightning as the default general assistant.

Recommended Workload Routing

Repo / coding agentsYi-Lightning

Higher SWE-bench (63.4%).

High-volume chatYi-Lightning

Lower output list price ($0.14/1M).

Voice / low-latency UIYi-Lightning

Lower TTFT (150 ms).

Long-document RAGDeepSeek Coder V2

Larger window (128k).

Screenshots / visionYi-Lightning

Yi-Lightning is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Yi-Lightning	Higher SWE-bench (63.4%).
High-volume chat	Yi-Lightning	Lower output list price ($0.14/1M).
Voice / low-latency UI	Yi-Lightning	Lower TTFT (150 ms).
Long-document RAG	DeepSeek Coder V2	Larger window (128k).
Screenshots / vision	Yi-Lightning	Yi-Lightning is the side marked multimodal in the catalog.

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CompareLLM Matrix

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LIVE

DeepSeek

DeepSeek Coder V2

Elo 1,365

LiveBench58.6%

SWE-bench60.5%

Speed75 tok/s

Output cost$0.28/1M

01.AI

Yi-Lightning

Elo 1,475

LiveBench65%

SWE-bench63.4%

Speed130 tok/s

Output cost$0.14/1M

Frequently Asked Questions

Which is better overall, DeepSeek Coder V2 or Yi-Lightning?: Yi-Lightning has the higher preference Elo in our latest snapshot (1,475). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, DeepSeek Coder V2 or Yi-Lightning?: Yi-Lightning leads SWE-bench at 63.4% vs 60.5%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Yi-Lightning output tokens are $0.14/1M versus $0.28/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek Coder V2 or Yi-Lightning?: Yi-Lightning has the lower time-to-first-token (150 ms vs 290 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: DeepSeek Coder V2 accepts 128k tokens versus 16k.
Can I self-host either model?: DeepSeek Coder V2 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 Coder V2 and Yi-Lightning Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All DeepSeek Coder V2 matchups →|All Yi-Lightning matchups →

DeepSeek Coder V2 vs DeepSeek V3 (next deepseek)Yi-Lightning vs Yi-Large (previous other)Yi-Lightning vs Ernie 4.5 Turbo (next other)DeepSeek V4 Flash vs Yi-Lightning DeepSeek V4 Pro vs Yi-Lightning DeepSeek R1 vs DeepSeek Coder V2

DeepSeek Coder V2 vs Yi-Lightning benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek Coder V2 (1)vsYi-Lightning (8)

DeepSeek Coder V2: 1W (11%)Overall: Yi-LightningYi-Lightning: 8W (89%)

← DeepSeek Coder V21 tiesYi-Lightning →

Yi-Lightning (5/5)

Intelligence & Reasoning

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

Preference Elo

1,365vs1,475

Coding Elo

1,442vs1,480

SWE-bench

60.5%vs63.4%

LiveBench

58.6%vs65%

GPQA Diamond

70.2%vs78%

DeepSeek Coder V2: 0WYi-Lightning: 5W

Yi-Lightning (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

75 tok/svs130 tok/s

Time to first token

290 msvs150 ms

DeepSeek Coder V2: 0WYi-Lightning: 2W

Tied (1/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.28/1Mvs$0.14/1M

Input price

$0.14/1Mvs$0.14/1M

Context window

128kvs16k

DeepSeek Coder V2: 1WYi-Lightning: 1W

Recommended Workload Routing

Repo / coding agentsYi-Lightning

Higher SWE-bench (63.4%).

High-volume chatYi-Lightning

Lower output list price ($0.14/1M).

Voice / low-latency UIYi-Lightning

Lower TTFT (150 ms).

Long-document RAGDeepSeek Coder V2

Larger window (128k).

Screenshots / visionYi-Lightning

Yi-Lightning is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Yi-Lightning	Higher SWE-bench (63.4%).
High-volume chat	Yi-Lightning	Lower output list price ($0.14/1M).
Voice / low-latency UI	Yi-Lightning	Lower TTFT (150 ms).
Long-document RAG	DeepSeek Coder V2	Larger window (128k).
Screenshots / vision	Yi-Lightning	Yi-Lightning is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek Coder V2 or Yi-Lightning?

Yi-Lightning has the higher preference Elo in our latest snapshot (1,475). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, DeepSeek Coder V2 or Yi-Lightning?

Yi-Lightning leads SWE-bench at 63.4% vs 60.5%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Yi-Lightning output tokens are $0.14/1M versus $0.28/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek Coder V2 or Yi-Lightning?

Yi-Lightning has the lower time-to-first-token (150 ms vs 290 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

DeepSeek Coder V2 accepts 128k tokens versus 16k.

Can I self-host either model?

DeepSeek Coder V2 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 Coder V2 and Yi-Lightning Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.