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Every score has a dated snapshot.

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  3. DeepSeek V3 vs OpenAI: GPT-5.6 Luna (batch)

Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

DeepSeek V3 vs OpenAI: GPT-5.6 Luna (batch) benchmark

In this head-to-head showdown, OpenAI: GPT-5.6 Luna (batch) is more budget-friendly at $0.6/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

Executive Comparison Verdict

Bottom Line: Choose DeepSeek V3 if your priority is peak reasoning, complex code generation, and top preference Elo. Choose OpenAI: GPT-5.6 Luna (batch) if you are optimizing for low latency, high throughput, and cost-efficient API deployment.
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Executive Verdict Summary

OpenAI: GPT-5.6 Luna (batch) holds empirical advantage (3 of 3 metrics)

Coding / SWESWE-bench
DeepSeek V3Top code solve rate
ReasoningGPQA / Live
DeepSeek V3Top logical accuracy
Best Value$/1M Tok
OpenAI: GPT-5.6 Luna (batch)Lowest API billing cost
Speed / TokTok/Sec
DeepSeek V3Fastest stream rate

Verified Advantage Breakdown

3 benchmarks evaluated across capability, speed, and cost

DeepSeek V3 (0)OpenAI: GPT-5.6 Luna (batch) (3)
DeepSeek V3
0 of 3 Wins
Competitive baseline across remaining benchmarks
OpenAI: GPT-5.6 Luna (batch)
3 of 3 Wins
✓Input price✓Output price✓Context window
DeepSeek
DeepSeek V3

Prior DeepSeek flagship. Baseline for v3 vs v4.

Elo 1,310In: $0.257 · Out: $1.029/1M
OpenAI
Leads 3 of 3
OpenAI: GPT-5.6 Luna (batch)

Auto-discovered from OpenRouter (openai/gpt-5.6-luna:batch). Preview until a second source matches.

In: $0.1 · Out: $0.6/1M
Top Rival Showdowns for DeepSeek V3
All Matchups
Compare vs:vs Claude Opus 4.5vs GPT-5vs Gemini 3 Provs Grok 4.6vs Qwen 3 Max
Preference Leader

No shared data

Single model data

Throughput Leader

No shared data

No latency data

Value per Dollar LeaderOpenAI: GPT-5.6 Luna (batch) Wins

OpenAI: GPT-5.6 Luna (batch)

$0.6 / 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.

DeepSeek V3 (6)vsOpenAI: GPT-5.6 Luna (batch) (3)
DeepSeek V3: 6W (67%)Overall: DeepSeek V3OpenAI: GPT-5.6 Luna (batch): 3W (33%)
← DeepSeek V3OpenAI: GPT-5.6 Luna (batch) →
🏆DeepSeek V3 Leads(4/5)

Intelligence & Reasoning

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

Benchmark
DeepSeek V3vsOpenAI: GPT-5.6 Luna (batch)
Preference Elo
1,310vs—
Coding Elo
—vs—
SWE-bench
48.6%vs—
LiveBench
55.4%vs—
GPQA Diamond
59.1%vs—
DeepSeek V3: 4WOpenAI: GPT-5.6 Luna (batch): 0W
🏆DeepSeek V3 Leads(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark
DeepSeek V3vsOpenAI: GPT-5.6 Luna (batch)
Output speed
66 tok/svs—
Time to first token
380 msvs—
DeepSeek V3: 2WOpenAI: GPT-5.6 Luna (batch): 0W
🏆OpenAI: GPT-5.6 Luna (batch) Leads(3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark
DeepSeek V3vsOpenAI: GPT-5.6 Luna (batch)
Output price
$1.029/1Mvs$0.6/1M+$0.429/1M
Input price
$0.257/1Mvs$0.1/1M+$0.157/1M
Context window
164kvs1.1M+886k
DeepSeek V3: 0WOpenAI: GPT-5.6 Luna (batch): 3W

Side-by-Side Benchmark Matrix

DeepSeek V3OpenAI: GPT-5.6 Luna (batch)
Preference Elo
DeepSeek V31,310
OpenAI: GPT-5.6 Luna (batch)—
LiveBench
DeepSeek V355.4%
OpenAI: GPT-5.6 Luna (batch)—
SWE-bench
DeepSeek V348.6%
OpenAI: GPT-5.6 Luna (batch)—
GPQA Diamond
DeepSeek V359.1%
OpenAI: GPT-5.6 Luna (batch)—
Time to first token
DeepSeek V3380 ms
OpenAI: GPT-5.6 Luna (batch)—
Output speed
DeepSeek V366 tok/s
OpenAI: GPT-5.6 Luna (batch)—
Input priceOpenAI: GPT-5.6 Luna (batch) +$0.157/1M
DeepSeek V3$0.257/1M
OpenAI: GPT-5.6 Luna (batch)$0.1/1M
Output priceOpenAI: GPT-5.6 Luna (batch) +$0.429/1M
DeepSeek V3$1.029/1M
OpenAI: GPT-5.6 Luna (batch)$0.6/1M
Context windowOpenAI: GPT-5.6 Luna (batch) +886k
DeepSeek V3164k
OpenAI: GPT-5.6 Luna (batch)1.1M
BenchmarkDeepSeek V3OpenAI: GPT-5.6 Luna (batch)Advantage Delta
Preference Elo
1,310
lmarena · Aug 17, 2026
——
LiveBench
55.4%
livebench · Aug 17, 2026
——
SWE-bench
48.6%
swebench · Aug 17, 2026
——
GPQA Diamond
59.1%
seed-bootstrap · Aug 1, 2026
——
Time to first token
380 ms
seed-bootstrap · Aug 1, 2026
——
Output speed
66 tok/s
seed-bootstrap · Aug 1, 2026
——
Input price
$0.257/1M
openrouter · Aug 17, 2026
$0.1/1M
openrouter · Aug 17, 2026
+$0.157/1M
Output price
$1.029/1M
openrouter · Aug 17, 2026
$0.6/1M
openrouter · Aug 17, 2026
+$0.429/1M
Context window
164k
openrouter · Aug 17, 2026
1.1M
openrouter · Aug 17, 2026
+886k

Workload Cost & Savings Calculator

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

Save 49% with OpenAI: GPT-5.6 Luna (batch)
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
OpenAI: GPT-5.6 Luna (batch)$12.50 / mo
In: $3.5Out: $9
Estimated Cost Delta

OpenAI: GPT-5.6 Luna (batch) is estimated to save $11.94/month ($143/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    OpenAI: GPT-5.6 Luna (batch):Pick OpenAI: GPT-5.6 Luna (batch) when you are optimizing output cost.
  • 2
    OpenAI: GPT-5.6 Luna (batch):Pick OpenAI: GPT-5.6 Luna (batch) for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatOpenAI: GPT-5.6 Luna (batch)

Lower output list price ($0.6/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.6 Luna (batch)

Larger window (1.1M).

Screenshots / visionOpenAI: GPT-5.6 Luna (batch)

OpenAI: GPT-5.6 Luna (batch) is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsinsufficient dataNeed SWE-bench on both sides.
High-volume chatOpenAI: GPT-5.6 Luna (batch)Lower output list price ($0.6/1M).
Voice / low-latency UIinsufficient dataNeed TTFT on both sides.
Long-document RAGOpenAI: GPT-5.6 Luna (batch)Larger window (1.1M).
Screenshots / visionOpenAI: GPT-5.6 Luna (batch)OpenAI: GPT-5.6 Luna (batch) is the side marked multimodal in the catalog.

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK
VS
DeepSeek

DeepSeek V3

Elo 1,310
SWE-bench48.6%
Speed (tok/s)66 tok/s
Input / 1M Tokens$0.257/1M
Output / 1M Tokens$1.029/1M
OpenAI

OpenAI: GPT-5.6 Luna (batch)

Elo n/a
SWE-bench—
Speed (tok/s)1.1M
Input / 1M Tokens$0.1/1M
Output / 1M Tokens$0.6/1M

Frequently Asked Questions

Which is better overall, DeepSeek V3 or OpenAI: GPT-5.6 Luna (batch)?
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 OpenAI: GPT-5.6 Luna (batch)?
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?
OpenAI: GPT-5.6 Luna (batch) output tokens are $0.6/1M versus $1.029/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek V3 or OpenAI: GPT-5.6 Luna (batch)?
We do not have TTFT for both models.
Which has the larger context window?
OpenAI: GPT-5.6 Luna (batch) accepts 1.1M tokens versus 164k.
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 OpenAI: GPT-5.6 Luna (batch) 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 OpenAI: GPT-5.6 Luna (batch) matchups →
DeepSeek V3 vs DeepSeek Coder V2 (previous deepseek)DeepSeek V3 vs DeepSeek R1 (next deepseek)GPT-5 vs DeepSeek V3DeepSeek V4 Pro vs DeepSeek V3GPT-4.5 Orion vs DeepSeek V3GPT-5.6 Sol vs DeepSeek V3