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© 2026 CompareLLM. Public benchmark data aggregated from Arena Elo, LiveBench, SWE-bench & OpenRouter.

Every score has a dated snapshot.

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  3. Codestral 25.01 vs OpenAI: GPT-5.6 Luna (batch)

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

Codestral 25.01 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 Codestral 25.01 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
Codestral 25.01Top code solve rate
ReasoningGPQA / Live
Codestral 25.01Top logical accuracy
Best Value$/1M Tok
OpenAI: GPT-5.6 Luna (batch)Lowest API billing cost
Speed / TokTok/Sec
Codestral 25.01Fastest stream rate

Verified Advantage Breakdown

3 benchmarks evaluated across capability, speed, and cost

Codestral 25.01 (0)OpenAI: GPT-5.6 Luna (batch) (3)
Codestral 25.01
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
Mistral
Codestral 25.01

Mistral code-specialist model.

CodestralElo 1,320In: $0.3 · Out: $0.9/1M
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

Mistral Series Lineage & Sibling Variants

2 models

Currently comparing Codestral 25.01 vs OpenAI: GPT-5.6 Luna (batch). Alternative family tiers available.

Active: Codestral 25.01
Mistral Large 3$6
Top Rival Showdowns for Codestral 25.01
All Matchups
Compare vs:vs Claude Opus 4.5vs GPT-5vs Gemini 3 Provs Grok 4.6vs DeepSeek V4 Pro
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.

Codestral 25.01 (7)vsOpenAI: GPT-5.6 Luna (batch) (3)
Codestral 25.01: 7W (70%)Overall: Codestral 25.01OpenAI: GPT-5.6 Luna (batch): 3W (30%)
← Codestral 25.01OpenAI: GPT-5.6 Luna (batch) →
🏆Codestral 25.01 Leads(5/5)

Intelligence & Reasoning

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

Benchmark
Codestral 25.01vsOpenAI: GPT-5.6 Luna (batch)
Preference Elo
1,320vs—
Coding Elo
1,402vs—
SWE-bench
51.8%vs—
LiveBench
54%vs—
GPQA Diamond
58.4%vs—
Codestral 25.01: 5WOpenAI: GPT-5.6 Luna (batch): 0W
🏆Codestral 25.01 Leads(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark
Codestral 25.01vsOpenAI: GPT-5.6 Luna (batch)
Output speed
148 tok/svs—
Time to first token
150 msvs—
Codestral 25.01: 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
Codestral 25.01vsOpenAI: GPT-5.6 Luna (batch)
Output price
$0.9/1Mvs$0.6/1M+$0.3/1M
Input price
$0.3/1Mvs$0.1/1M+$0.2/1M
Context window
256kvs1.1M+794k
Codestral 25.01: 0WOpenAI: GPT-5.6 Luna (batch): 3W

Side-by-Side Benchmark Matrix

Codestral 25.01OpenAI: GPT-5.6 Luna (batch)
Preference Elo
Codestral 25.011,320
OpenAI: GPT-5.6 Luna (batch)—
Coding Elo
Codestral 25.011,402
OpenAI: GPT-5.6 Luna (batch)—
LiveBench
Codestral 25.0154%
OpenAI: GPT-5.6 Luna (batch)—
SWE-bench
Codestral 25.0151.8%
OpenAI: GPT-5.6 Luna (batch)—
GPQA Diamond
Codestral 25.0158.4%
OpenAI: GPT-5.6 Luna (batch)—
Time to first token
Codestral 25.01150 ms
OpenAI: GPT-5.6 Luna (batch)—
Output speed
Codestral 25.01148 tok/s
OpenAI: GPT-5.6 Luna (batch)—
Input priceOpenAI: GPT-5.6 Luna (batch) +$0.2/1M
Codestral 25.01$0.3/1M
OpenAI: GPT-5.6 Luna (batch)$0.1/1M
Output priceOpenAI: GPT-5.6 Luna (batch) +$0.3/1M
Codestral 25.01$0.9/1M
OpenAI: GPT-5.6 Luna (batch)$0.6/1M
Context windowOpenAI: GPT-5.6 Luna (batch) +794k
Codestral 25.01256k
OpenAI: GPT-5.6 Luna (batch)1.1M
BenchmarkCodestral 25.01OpenAI: GPT-5.6 Luna (batch)Advantage Delta
Preference Elo
1,320
lmarena · Aug 17, 2026
——
Coding Elo
1,402
lmarena · Aug 17, 2026
——
LiveBench
54%
livebench · Aug 17, 2026
——
SWE-bench
51.8%
swebench · Aug 17, 2026
——
GPQA Diamond
58.4%
seed-bootstrap · Aug 1, 2026
——
Time to first token
150 ms
seed-bootstrap · Aug 1, 2026
——
Output speed
148 tok/s
seed-bootstrap · Aug 1, 2026
——
Input price
$0.3/1M
seed-bootstrap · Aug 1, 2026
$0.1/1M
openrouter · Aug 17, 2026
+$0.2/1M
Output price
$0.9/1M
seed-bootstrap · Aug 1, 2026
$0.6/1M
openrouter · Aug 17, 2026
+$0.3/1M
Context window
256k
seed-bootstrap · Aug 1, 2026
1.1M
openrouter · Aug 17, 2026
+794k

Workload Cost & Savings Calculator

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

Save 48% 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)
Codestral 25.01$24.00 / mo
In: $10.5Out: $13.5
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 $11.50/month ($138/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.

Related Editorial Dispatches & Benchmark Notes

View all news
launchJan 14, 2025

Codestral 25.01: Mistral’s code-specialist row

Jan 2025 code model. Still a valid cheap-coding compare. Not a chatbot.

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK
VS
Mistral

Codestral 25.01

Elo 1,320
SWE-bench51.8%
Speed (tok/s)148 tok/s
Input / 1M Tokens$0.3/1M
Output / 1M Tokens$0.9/1M
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, Codestral 25.01 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, Codestral 25.01 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 $0.9/1M. Input prices and retry rates still move the real bill.
Which is faster, Codestral 25.01 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 256k.
Can I self-host either model?
Neither model is marked open-weights here. You are comparing hosted APIs.
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. Codestral 25.01 and OpenAI: GPT-5.6 Luna (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Related news

  • launch · Jan 14, 2025

    Codestral 25.01: Mistral’s code-specialist row

Similar Head-to-Head Comparisons

All Codestral 25.01 matchups →|All OpenAI: GPT-5.6 Luna (batch) matchups →
Codestral 25.01 vs Mistral Large 3 (next mistral)GPT-5 vs Codestral 25.01GPT-4.5 Orion vs Codestral 25.01GPT-5.6 Sol vs Codestral 25.01GPT-5.6 Terra vs Codestral 25.01GPT-4o vs Codestral 25.01