Is GPT-5.6 Sol better than DeepSeek V4 Pro?

GPT-5.6 Sol (max) leads on quality: 65.4 vs 59.1. The BenchLeader Index combines every independent quality benchmark; GPT-5.6 Sol (max) is ahead overall as of 9 Nov 2026, but check the category scores for your use.

DeepSeek V4 Pro vs GPT-5.6 Sol: which is cheaper, and will that change?

DeepSeek V4 Pro is cheaper today: $0.990 against $8.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.

Is DeepSeek V4 Pro or GPT-5.6 Sol better for coding?

GPT-5.6 Sol scores higher in coding (66 vs 54 on the category index, where 50 is average). On SciCode, the top shared coding benchmark, it is 46.4% for DeepSeek V4 Pro against 57.1% for GPT-5.6 Sol.

Which is faster, DeepSeek V4 Pro or GPT-5.6 Sol?

GPT-5.6 Sol streams ~2× faster (99 vs 44 output tokens per second, Artificial Analysis 7-day median).

Which is better for long documents?

Both take about 1.1M tokens: DeepSeek V4 Pro 1,048,576, GPT-5.6 Sol 1,050,000.

Which has lower latency?

DeepSeek V4 Pro answers first: 1.5 s against 79.2 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.

When was DeepSeek V4 Pro released?

DeepSeek V4 Pro was released on 13 Aug 2026.

DeepSeek V4 Pro vs GPT-5.6 Sol

Full profiles: DeepSeek V4 Pro (DeepSeek) and GPT-5.6 Sol (OpenAI): every benchmark, price and rank.

Updated 9 Nov 2026 · Data from 12 sources

As of 9 Nov 2026, GPT-5.6 Sol is ahead of DeepSeek V4 Pro on quality (65.4 vs 59.1 on the BenchLeader Index), but DeepSeek V4 Pro is 8.1× cheaper at $0.990 vs $8.00 per 1M tokens blended. GPT-5.6 Sol leads in every category we measure both in. GPT-5.6 Sol streams ~2× faster.

Key facts (as of 9 Nov 2026)

DeepSeek V4 Pro scores 59.1 on the BenchLeader Index and GPT-5.6 Sol scores 65.4 (BenchLeader, 9 Nov 2026).
DeepSeek V4 Pro costs $0.990 per 1M tokens blended (list price, 9 Nov 2026).
GPT-5.6 Sol costs $8.00 per 1M tokens blended (list price, 9 Nov 2026).
GPT-5.6 Sol streams ~2× faster than DeepSeek V4 Pro (Artificial Analysis, 7-day median, 9 Nov 2026).
Of the 8 benchmarks both models have, GPT-5.6 Sol leads 8 (BenchLeader, 9 Nov 2026).

DeepSeek V4 Pro benchmarks high DeepSeek

GPT-5.6 Sol benchmarks max OpenAI Add a third model

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use case	Pick	Why	Confidence
Coding	GPT-5.6 Sol	66 vs 54 category score; SciCode 57.1% vs 46.4%	High
Maths	GPT-5.6 Sol	71 vs 65 category score; OTIS Mock AIME 100.0% vs 95.6%	Medium
Reasoning	GPT-5.6 Sol	65 vs 62 category score; GPQA Diamond 93.5% vs 90.9%	Medium
Chat quality (human preference)	–	Only DeepSeek V4 Pro has an Arena rating (65 category score)	Not comparable
Lowest cost	DeepSeek V4 Pro	$0.990 vs $8.00 per 1M blended; agentic coding session $0.048 vs $0.320	–
Fastest first answer	DeepSeek V4 Pro	1.5 s (DeepSeek V4 Pro (high)) vs 79.2 s (GPT-5.6 Sol (max)) to the first answer token	–
High volume on a budget	Neither flagship	A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs	–

Key differences

GPT-5.6 Sol (max) leads on quality: 65.4 vs 59.1.
DeepSeek V4 Pro (high) is stronger in human preference.
GPT-5.6 Sol (max) is stronger in coding, maths, reasoning, agents & tools, instruction following, knowledge, long context, multimodal.
DeepSeek V4 Pro (high) is 8.1× cheaper ($0.990 vs $8.00 per 1M blended).
GPT-5.6 Sol (max) streams 2.3× faster (99 vs 44 tokens per second).

At a glance

Spec	DeepSeek V4 Pro	GPT-5.6 Sol
Developer	DeepSeek	OpenAI
Released	13 Aug 2026	9 Jul 2026
Context window (tokens)	1,048,576	1,050,000
Compared at	DeepSeek V4 Pro (high)	GPT-5.6 Sol (max)
Open weights	Yes	No
Price in / out / cached input per 1M	$0.660 / $1.98 / $0.022	$4.00 / $20.00 / $0.400

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

Category	DeepSeek V4 Pro (high)	GPT-5.6 Sol (max)	Leader
Reasoning	62.2	64.9	GPT-5.6 Sol
Coding	53.8	65.9	GPT-5.6 Sol
Agents & tools	–	66.8	not comparable
Maths	64.6	70.7	GPT-5.6 Sol
Knowledge	–	64.3	not comparable
Instruction following	–	71.2	not comparable
Human preference	65.1	–	not comparable
Multimodal	–	65.9	not comparable
Long context	–	66.8	not comparable

On one chart

Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.

Not drawn, measured for fewer than two of these models: Agents & tools, Knowledge, Instruction following, Long context, Multimodal, Human preference.

ModelIndex

Where sources disagree

Across the 8 benchmarks both have, DeepSeek V4 Pro leads 0, GPT-5.6 Sol leads 8. Every overall index that rates both puts GPT-5.6 Sol ahead.

Overall index	DeepSeek V4 Pro (high)	GPT-5.6 Sol (max)	Leader
BenchLeader Index	59.1	65.4	GPT-5.6 Sol
Arena Text	1464	1485†	GPT-5.6 Sol

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.

Measure	DeepSeek V4 Pro (high)	GPT-5.6 Sol (max)
Blended price per 1M tokens	$0.990	$8.00
Input / output per 1M	$0.660 / $1.98	$4.00 / $20.00
Cached input per 1M	$0.022	$0.400
Price per task: chat reply	$0.0009	$0.0076
Price per task: summarize a 30-page report	$0.0091	$0.060
Price per task: code edit	$0.0069	$0.054
Price per task: agentic coding session	$0.048	$0.320
Price per task: structured extraction	$0.0017	$0.012
Agentic coding session, input mostly cached	$0.019	$0.158
Output speed	44 tok/s	99 tok/s
Time to first answer	1.5 s	79.2 s
Time to a complete answer	–	162.8 s

Each model is compared at its best-ranked reasoning-effort setting. DeepSeek V4 Pro (high) scores 59.1 and takes 1 s to its first answer token; DeepSeek V4 Pro (max) scores 56.9 in 74 s, DeepSeek V4 Pro scores 53.3 in 1 s. GPT-5.6 Sol (max) scores 65.4 and takes 79 s to its first answer token; GPT-5.6 Sol (xhigh) scores 64.2 in 31 s, GPT-5.6 Sol (high) scores 63.5 in 13 s. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

158 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

Metric	Publisher	DeepSeek V4 Pro (high)	GPT-5.6 Sol (max)
BenchLeader Index	BenchLeader	59.1	65.4
Coding score	BenchLeader	53.8	65.9
Human preference score	BenchLeader	65.1	–
Maths score	BenchLeader	64.6	70.7
Reasoning score	BenchLeader	62.2	64.9
Agents & tools score	BenchLeader	–	66.8
Instruction following score	BenchLeader	–	71.2
Knowledge score	BenchLeader	–	64.3
Long context score	BenchLeader	–	66.8
Multimodal score	BenchLeader	–	65.9
Blended price $/M	BenchLeader	$0.990	$8.00
Output speed	BenchLeader	44 tok/s	99 tok/s
Time to first answer	BenchLeader	1.5 s	79.2 s
Context window	BenchLeader	1,048,576 tokens	1,050,000 tokens
Reasoning
GPQA Diamond	Epoch AI Benchmarking Hub	90.9%	93.5%
SimpleBench	SimpleBench	–	64.8%†
Arena Hard Prompts	Arena (LMArena)	1482	1511†
LiveBench 1.0 Reasoning	LiveBench	85.8%†	91.7%
GPQA Diamond (AA)	Artificial Analysis	92.8%†	94.1%
Humanity's Last Exam (AA)	Artificial Analysis	41.0%†	49.5%
HLE-Diamond (AA)	Artificial Analysis	19.5%†	–
GPQA Diamond (Vals)	Vals AI	92.4%†	95.2%
EnigmaEval	Scale AI SEAL	–	37.1%†
Kagi LLM Benchmark	Kagi LLM Benchmark	53.5%†	67.0%†
ARC-AGI-1	ARC Prize	87.2%	96.5%
ARC-AGI-2	ARC Prize	59.7%	92.5%
ARC-AGI-3	ARC Prize	–	7.8%
CritPt	Artificial Analysis	18.0%†	32.3%
CritPt v2 hard subset (AA)	Artificial Analysis	23.5%†	60.0%
MysteryMechanism	Vals AI	–	33.3%
Chess Puzzles	Epoch AI Benchmarking Hub	16.0%	59.0%
Mystery Game Puzzles	Epoch AI Benchmarking Hub	43.0%†	58.0%
CL-bench Life	Epoch AI Benchmarking Hub	13.5%	–
LMCA	Epoch AI Benchmarking Hub	45.5%†	58.4%
DTBench	Epoch AI Benchmarking Hub	93.9%†	95.5%
ForecastBench	ForecastBench	60.7%†	65.5%
BTF-3	Epoch AI Benchmarking Hub	–	13.7%
Coding
SWE-bench Verified (Epoch)	Epoch AI Benchmarking Hub	77.6%†	–
SciCode	SciCode	46.4%	57.1%

Show all 158 benchmarks

Metric	Publisher	DeepSeek V4 Pro (high)	GPT-5.6 Sol (max)
Coding
WeirdML	WeirdML	46.5%	87.0%
FrontierCode	Cognition	28.6%	47.5%†
GSO-Bench	GSO-Bench	–	76.5%†
Arena Coding	Arena (LMArena)	1503	1533†
Arena WebDev	Arena (LMArena)	1581	1615†
LiveBench 1.0 Coding	LiveBench	77.2%†	83.9%
SciCode (AA)	Artificial Analysis	51.0%†	57.1%
LiveCodeBench	Vals AI	87.5%†	82.6%
IOI	Vals AI	51.6%†	91.2%
SWE-bench (Vals)	Vals AI	96.4%†	96.2%
Code Migration	Vals AI	41.5%†	52.9%
Code Migration v1.1	Vals AI	52.0%†	–
ProgramBench	Vals AI	0.0%†	1.5%
Vibe Code Bench 1-100	Vals AI	17.5%†	20.0%
Vibe Code Bench v1.1	Vals AI	82.3%†	80.5%
SWE Atlas: Codebase QnA	Scale AI SEAL	27.1%†	46.0%†
SWE Atlas: Test Writing	Scale AI SEAL	27.1%†	45.9%†
MirrorCode	Epoch AI Benchmarking Hub	–	20.0%†
Surface Evolver Bench	Epoch AI Benchmarking Hub	40.0%	93.1%†
DeepSWE v1.1	Epoch AI Benchmarking Hub	–	72.7%
CursorBench	Cursor	–	41.7%
ALE-Bench	Epoch AI Benchmarking Hub	1006.1	2176.9
FrontierSWE	Epoch AI Benchmarking Hub	–	32.2%
Terminal-Bench 4.0 (AA)	Artificial Analysis	14.1%†	39.9%
Terminal-Bench 2.1 (AA)	Artificial Analysis	78.7%†	88.0%
Startrise Frontend	Startrise	62.7%†	66.2%†
GameBench 2 Overall	DuelLab GameBench 2	42.0†	66.7†
GameBench 2 by reasoning setting	DuelLab GameBench 2	45.0	79.6†
Design Arena Website	Design Arena	1231†	1317†
FrontierCode 1.1 (AA)	Artificial Analysis	38.8%†	–
FrontierCode 2.0 (AA)	Artificial Analysis	17.1%†	–
Agents & tools
Terminal-Bench	Terminal-Bench	–	38.5%
OSWorld-Verified 2.0	OSWorld	–	27.3%
APEX-Agents	Mercor	47.3%†	51.4%†
Arena Agent	Arena (LMArena)	–	4.5†
LiveBench Agentic Coding	LiveBench	55.0%†	56.2%
Terminal-Bench Hard	Artificial Analysis	–	65.9%
τ²-Bench Telecom (AA)	Artificial Analysis	–	85.1%
Terminal-Bench 2.1 (Vals)	Vals AI	50.2%†	85.8%
HiL-Bench	Scale AI SEAL	38.5%†	32.3%†
τ³-bench Banking	τ²-bench	–	46.9%†
GDPval-AA v2.1, normalised score	Artificial Analysis	47.5%†	–
GDPval-AA v2.1	Artificial Analysis	1457†	–
τ³-Banking (AA)	Artificial Analysis	39.6%†	44.3%
ITBench SRE (AA)	Artificial Analysis	–	56.2%
Analyst Agent (AA)	Artificial Analysis	–	47.5%
CUA-bench	Vals AI	–	8.3%
CyberBench	Vals AI	72.9%†	76.3%
Finance Agent v2	Vals AI	50.4%†	53.8%
Finance Agent v2.1	Vals AI	57.1%†	–
Harvey's Legal Agent Benchmark v1.1	Vals AI	10.8%†	–
Harvey's Legal Agent Benchmark v1	Vals AI	7.5%†	2.5%
Legal Research Bench	Vals AI	40.9%†	48.1%
SkillsBench	Vals AI	53.8%†	54.1%
SREBench	Vals AI	1.9%†	30.5%
Tax Agent Bench	Vals AI	26.8%†	31.1%
Terminal-Bench 2.0 (Vals)	Vals AI	56.2%†	–
Terminal-Bench 4.0 (Vals)	Vals AI	14.1%†	37.9%
Terminal-Bench Science	Vals AI	4.3%†	20.0%
Time Horizon Index: KSP	Vals AI	–	23.8%
Web Search Index	Vals AI	–	43.6%
Arena Search	Arena (LMArena)	–	1256†
BALROG	BALROG	–	60.0%
PostTrainBench	Epoch AI Benchmarking Hub	–	36.2%
GBAEval	Epoch AI Benchmarking Hub	–	52.6%†
Vending-Bench 2	Andon Labs	3284.5†	9619.4†
AutomationBench	Artificial Analysis	56.7%†	60.1%
GDP.pdf (AA)	Artificial Analysis	11.4%†	27.2%
EnterpriseOps-Gym	Artificial Analysis	49.6%†	42.9%
AA-Briefcase v1.1	Artificial Analysis	1253†	1479
Design Arena Agentic	Design Arena	921†	1236†
Terminal-Bench-Science 0.1 (AA)	Artificial Analysis	5.7%†	22.4%
Maths
FrontierMath Tiers 1–3	Epoch AI Benchmarking Hub	64.6%†	89.1%
FrontierMath Tier 4	Epoch AI Benchmarking Hub	26.8%†	82.9%
OTIS Mock AIME	Epoch AI Benchmarking Hub	95.6%	100.0%
ProofBench	Vals AI	50.0%†	83.0%
LiveBench Mathematics	LiveBench	95.1%†	96.2%
AIME 2026	MathArena	96.7%†	–
HMMT February 2026	MathArena	93.9%†	–
USAMO 2026	MathArena	60.7%†	–
MathArena Apex	MathArena	28.1%†	–
Arena Maths	Arena (LMArena)	1465	1494†
Knowledge
SimpleQA Verified	Epoch AI Benchmarking Hub	52.9%†	69.7%
LiveBench 1.0 Data Analysis	LiveBench	79.2%†	79.8%
AA-Omniscience v1.1	Artificial Analysis	-6.4†	–
MMLU-Pro	Vals AI	87.3%†	89.1%
LegalBench	Vals AI	82.4%†	87.0%
CorpFin	Vals AI	65.4%†	64.4%
TaxEval	Vals AI	73.1%†	74.8%
PRBench Finance	Scale AI SEAL	–	50.5%
PRBench Legal	Scale AI SEAL	–	50.5%
BioMysteryBench	Vals AI	–	71.1%
CaseLaw v2	Vals AI	59.4%†	–
Excel Modeling Benchmark	Vals AI	52.8%†	72.3%
Excel Modeling Benchmark v1.1	Vals AI	65.1%†	–
MedCode	Vals AI	42.5%†	44.0%
MedScribe	Vals AI	80.2%†	85.2%
Public Benefits Bench v1.1	Vals AI	62.9%†	66.5%
DrugDiscoveryBench	Scale AI SEAL	31.7%†	56.5%
EBR-bench	Epoch AI Benchmarking Hub	–	44.8%
GDP.pdf	Epoch AI Benchmarking Hub	–	30.7%
AA-Omniscience v1.1: accuracy	Artificial Analysis	45.2%†	–
AA-Omniscience v1.1: non-hallucination	Artificial Analysis	5.9%†	–
Instruction following
LiveBench Language	LiveBench	82.1%†	87.7%
LiveBench Instruction Following	LiveBench	67.7%†	71.8%
IFBench	Artificial Analysis	–	72.7%
Arena Instruction Following	Arena (LMArena)	1461	1490†
Human preference
Arena Text	Arena (LMArena)	1464	1485†
EQ-Bench 4	EQ-Bench	1156†	1236†
Arena Creative Writing	Arena (LMArena)	1444	1471†
Arena Multi-turn	Arena (LMArena)	1469	1491†
Arena Longer Queries	Arena (LMArena)	1474	1498†
Multimodal
Arena Vision	Arena (LMArena)	–	1282†
MMMU-Pro	Artificial Analysis	–	83.4%
MMMU-Pro (Vals)	Vals AI	–	88.8%
MortgageTax	Vals AI	–	67.3%
Blueprint-Bench 2	Epoch AI Benchmarking Hub	–	33.6%†
Long context
AA-LCR v1.1	Artificial Analysis	80.3%†	84.0%
Arena Document	Arena (LMArena)	–	1486†
MLCR	Artificial Analysis	–	30.0%
Composite
Epoch Capabilities Index	Epoch AI Benchmarking Hub	155.9†	163.0†
LiveBench 1.0	LiveBench	77.4%†	81.0%
AA Intelligence Index v5.0	Artificial Analysis	23.1†	–
AA Intelligence Index v4.3.2	Artificial Analysis	36†	47.0
AA Progress Index v1	Artificial Analysis	311.5†	331.5
Vals Index	Vals AI	53.0†	–
Vals Finance Index	Vals AI	52.9%†	–
Vals RSI Index	Vals AI	–	23.9%
Vals Science Index	Vals AI	–	41.5%
Vals Multimodal Index	Vals AI	–	72.6%
Vals Router Index	Vals AI	53.0%†	–
Safety & honesty
FORTRESS	Scale AI SEAL	–	20.1%†
Metadata
AA Openness Index	Artificial Analysis	44.4†	–

Data as of 2026-11-09. Best configuration of each model; every score links to its source on the model pages.

DuelLab GameBench 2, release gb2-20261103-eaea31df94e6 (https://benchmarks.duellab.org/releases/gb2-20261103-eaea31df94e6/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.

What changed

9 Nov 2026 DeepSeek V4 Pro (high): BenchLeader Index 57.5 → 59.1.
9 Nov 2026 GPT-5.6 Sol (max): 1 score revision.
5 Nov 2026 DeepSeek V4 Pro (high): 1 score revision.
4 Nov 2026 DeepSeek V4 Pro (high): 1 score revision.
4 Nov 2026 GPT-5.6 Sol (max): 1 score revision.
28 Oct 2026 GPT-5.6 Sol (max): 2 new results (AA Progress Index v1, CritPt v2 hard subset (AA)).
25 Oct 2026 GPT-5.6 Sol (max): 1 new result (AA-Briefcase v1.1).
23 Oct 2026 GPT-5.6 Sol (max): 3 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index, Vals Science Index).
21 Oct 2026 DeepSeek V4 Pro (high): 16 new results (GPQA Diamond, OTIS Mock AIME, SciCode…); input price moved from $0.44/M to $0.66/M (50% up); output price moved from $0.87/M to $1.98/M (128% up).
21 Oct 2026 GPT-5.6 Sol (max): 1 score revision.

Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs