Model comparison

DeepSeek V3 vs Mistral Medium 3.5 128B

Data verified July 27, 2026

Head-to-head evidence from 16 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

DeepSeek V3

DeepSeek

44.15/100

No comparison

Mistral Medium 3.5 128B

Mistral

N/A

0 category wins1 category wins

Public leaderboard positions: DeepSeek V3 #154 (Supported); Mistral Medium 3.5 128B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V3 and Mistral Medium 3.5 128B share 16 comparable benchmark results. 1 of 8 categories are comparable. 6 results are unique to DeepSeek V3; 9 to Mistral Medium 3.5 128B.

Updated July 27, 2026

Shared results: 16
DeepSeek V3 only: 6
Mistral Medium 3.5 128B only: 9
Comparable categories: 1 / 8

Treat this as a split decision. DeepSeek V3 makes more sense if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model; Mistral Medium 3.5 128B is the better fit if coding is the priority or you need the larger 256K context window.

Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 5 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

DeepSeek V3 and Mistral Medium 3.5 128B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

Mistral Medium 3.5 128B is also the more expensive model on tokens at $1.50 input / $7.50 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek V3. That is roughly 6.8x on output cost alone. Mistral Medium 3.5 128B is the reasoning model in the pair, while DeepSeek V3 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Mistral Medium 3.5 128B gives you the larger context window at 256K, compared with 128K for DeepSeek V3.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for DeepSeek V3 and Mistral Medium 3.5 128B
Category	DeepSeek V3	Δ	Mistral Medium 3.5 128B
Coding	DeepSeek V338.9	Margin→ 38.7	Mistral Medium 3.5 128B77.6
Knowledge	DeepSeek V372.7	MarginNo overlap	Mistral Medium 3.5 128BNot measured
Math	DeepSeek V31.7	MarginNo overlap	Mistral Medium 3.5 128BNot measured
Inst. Following	DeepSeek V386.1	MarginNo overlap	Mistral Medium 3.5 128BNot measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

A · DeepSeek V3B · Mistral Medium 3.5 128B

SWE-bench Verified
Coding
Source ↗
A 42%B 77.6%
Winner: Mistral Medium 3.5 128BΔ 35.6
SWE-bench Verified: DeepSeek V3 scored 42%; Mistral Medium 3.5 128B scored 77.6%. Mistral Medium 3.5 128B wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

Metric	DeepSeek V3	Mistral Medium 3.5 128B	Comparison
Input / output priceUSD per 1M tokens	DeepSeek V3$0.27 input / $1.1 output	Mistral Medium 3.5 128B$1.5 input / $7.5 output	DeepSeek V3 has the lower combined listed price.
Generation speedtokens per second	DeepSeek V3Not available	Mistral Medium 3.5 128BNot available	A complete speed comparison is not available.
First-answer latencyseconds to first token	DeepSeek V3Not available	Mistral Medium 3.5 128BNot available	A complete latency comparison is not available.
Context windowmaximum listed tokens	DeepSeek V3128K	Mistral Medium 3.5 128B256K	Mistral Medium 3.5 128B lists the larger context window.

Benchmark Deep Dive

Agentic

11 benchmarks

Benchmark	DeepSeek V3	Mistral Medium 3.5 128B	Result
AA Agentic IndexSource	1.6%	19.0%	Mistral Medium 3.5 128B leads
τ²-bench resultsSource	22.8%	94.2%	Mistral Medium 3.5 128B leads
GDPval-AASource	0.0%	21.6%	Mistral Medium 3.5 128B leads
GDPval-AASource	231	933	Mistral Medium 3.5 128B leads
τ³-bench resultsSource	—	91.4%	Not comparable
Gert LabsSource	—	39.10%	Not comparable
AA EnterpriseOps-GymSource	—	33.7%	Not comparable
AA Harvey LABSource	—	69.1%	Not comparable
terminalBenchHardSource	—	33.3%	Not comparable
AA BriefcaseSource	—	516	Not comparable
AA Tau3 BankingSource	—	14.4%	Not comparable

CodingMistral Medium 3.5 128B wins

4 benchmarks

Benchmark	DeepSeek V3	Mistral Medium 3.5 128B	Result
LiveCodeBenchSource	37.6%	—	Not comparable
SWE-bench VerifiedSource	42%	77.6%	Mistral Medium 3.5 128B leads
AA Coding IndexSource	23.0%	46.9%	Mistral Medium 3.5 128B leads
AA-SciCodeSource	35.4%	39.6%	Mistral Medium 3.5 128B leads

Reasoning

2 benchmarks

Benchmark	DeepSeek V3	Mistral Medium 3.5 128B	Result
AA-LCRSource	29.0%	61.0%	Mistral Medium 3.5 128B leads
CritPtSource	0.0%	0.0%	Tie

Knowledge

9 benchmarks

Benchmark	DeepSeek V3	Mistral Medium 3.5 128B	Result
GPQASource	59.1%	—	Not comparable
MMLU-ProSource	75.9%	—	Not comparable
Artificial Analysis Intelligence IndexSource	14.2%	29.9%	Mistral Medium 3.5 128B leads
AA-GPQA DiamondSource	55.7%	74.8%	Mistral Medium 3.5 128B leads
AA-HLESource	3.6%	12.8%	Mistral Medium 3.5 128B leads
AA-Omniscience IndexSource	-41.3%	-36.3%	Mistral Medium 3.5 128B leads
AA-Omniscience AccuracySource	25.4%	25.1%	DeepSeek V3 leads
AA-Omniscience Hallucination RateSource	89.4%	82.0%	Mistral Medium 3.5 128B leads
AA Openness IndexSource	—	33.3%	Not comparable

Math

1 benchmarks

Benchmark	DeepSeek V3	Mistral Medium 3.5 128B	Result
FrontierMath v2 (Tiers 1-3)Source	1.724%	—	Not comparable

Multimodal

2 benchmarks

Benchmark	DeepSeek V3	Mistral Medium 3.5 128B	Result
Design Arena WebsiteSource	1145	—	Not comparable
AA-MMMU-ProSource	—	64.9%	Not comparable

Inst. Following

2 benchmarks

Benchmark	DeepSeek V3	Mistral Medium 3.5 128B	Result
IFEvalSource	86.1%	—	Not comparable
AA-IFBenchSource	34.8%	68.8%	Mistral Medium 3.5 128B leads

Frequently Asked Questions (2)

Which is better, DeepSeek V3 or Mistral Medium 3.5 128B?

DeepSeek V3 and Mistral Medium 3.5 128B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for coding, DeepSeek V3 or Mistral Medium 3.5 128B?

Mistral Medium 3.5 128B has the edge for coding in this comparison, averaging 77.6 versus 38.9. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

DeepSeek V3

API / mo$1,028

Self-host / mo$18,221

Break-even1.2B/day

Mistral Medium 3.5 128B

API / mo$6,750

Self-host / moNot listed

Break-even—

Proprietary model — self-hosting not applicable.

Model the full break-even

Related Comparisons

Explore More

DeepSeek Compare Pricing Methodology Find Your Best LLM Overall Rankings

Last updated: July 27, 2026

Know when it’s worth switching models

The model to choose, the cheaper alternative, and the release we would wait on.

One email each week. Unsubscribe anytime.