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Compare/DeepSeek V4.1 Flash (Reasoning, Max Effort) vs MiniMax-M2.5

DeepSeek V4.1 Flash (Reasoning, Max Effort)vsMiniMax-M2.5

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

DeepSeek

DeepSeek V4.1 Flash (Reasoning, Max Effort)

Input
$0.3/M
Output
$1.2/M
Speed
223 tok/s
TTFT
1.19s
MiniMax

MiniMax-M2.5

Input
$0.3/M
Output
$1.2/M
Speed
93 tok/s
TTFT
1.68s

Winner by Category

Cheaper
Tie
Faster (tok/s)
DeepSeek V4.1 Flash (Reasoning, Max Effort)
Lower Latency
DeepSeek V4.1 Flash (Reasoning, Max Effort)
Benchmarks (1-0)
DeepSeek V4.1 Flash (Reasoning, Max Effort)

Pricing Comparison

MetricDeepSeek V4.1 Flash (Reasoning, Max Effort)MiniMax-M2.5
Input ($/M tokens)$0.3$0.3
Output ($/M tokens)$1.2$1.2
Cost for 1M input + 100K output tokens:
DeepSeek V4.1 Flash (Reasoning, Max Effort)$0.42
MiniMax-M2.5$0.42

Speed Comparison

Output Speed (tokens/s) — higher is better
DeepSeek V4.1 Flash (Reasoning, Max Effort)
223 tok/s
MiniMax-M2.5
93 tok/s
Time to First Token (seconds) — lower is better
DeepSeek V4.1 Flash (Reasoning, Max Effort)
1.19s
MiniMax-M2.5
1.68s

Editorial Analysis

Verdict. DeepSeek V4.1 Flash (Reasoning, Max Effort) wins the overall benchmark matchup 1–0 across 1 overlapping categories, but raw benchmark score is only one input to the decision.

Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, MiniMax-M2.5 is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). MiniMax-M2.5 makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. DeepSeek V4.1 Flash (Reasoning, Max Effort) is strongest on Intelligence Index (39.5). MiniMax-M2.5 leads on Intelligence Index (22.8).

Speed. On throughput, DeepSeek V4.1 Flash (Reasoning, Max Effort) generates tokens at 223 tok/s versus 93 tok/s — about 58% faster. On time-to-first-token, DeepSeek V4.1 Flash (Reasoning, Max Effort) responds in 1190ms vs 1680ms, which matters most for chat-style UIs.

Provider. DeepSeek and MiniMax sell to overlapping but distinct developer audiences: DeepSeek tends to ship frontier reasoning models with premium positioning, while MiniMax often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.

Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): DeepSeek V4.1 Flash (Reasoning, Max Effort) costs $27.00 ($324/year); MiniMax-M2.5 costs $27.00 ($324/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): DeepSeek V4.1 Flash (Reasoning, Max Effort) ≈ $3.90/run, MiniMax-M2.5 ≈ $3.90/run. At agent/realtime scale (200M input / 100M output per million requests): DeepSeek V4.1 Flash (Reasoning, Max Effort) ≈ $180/run, MiniMax-M2.5 ≈ $180/run.

Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.

Head-to-head deltas

  • On throughput, DeepSeek V4.1 Flash (Reasoning, Max Effort) is 2.38× faster (223 tok/s vs 93 tok/s). For streaming chat or real-time agents this alone often flips the recommendation.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
39.522.8
Coding Index
——
Math Index
——
GPQA Diamond
——
MMLU-Pro
——
LiveCodeBench
——
AIME 2025
——
MATH-500
——
Humanity's Last Exam
——
SciCode
——
IFBench
——
TerminalBench
——
DeepSeek V4.1 Flash (Reasoning, Max Effort)1 wins
0 winsMiniMax-M2.5

Frequently Asked Questions

Which is cheaper, DeepSeek V4.1 Flash (Reasoning, Max Effort) or MiniMax-M2.5?

Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.

Which model performs better on benchmarks?

DeepSeek V4.1 Flash (Reasoning, Max Effort) wins 1 out of 12 benchmarks compared to 0 for MiniMax-M2.5. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

DeepSeek V4.1 Flash (Reasoning, Max Effort) generates tokens faster at 223 tok/s vs 93 tok/s. DeepSeek V4.1 Flash (Reasoning, Max Effort) also has lower time-to-first-token (1.19s vs 1.68s).

When should I use DeepSeek V4.1 Flash (Reasoning, Max Effort) vs MiniMax-M2.5?

Choose based on your priorities: both are similarly priced, DeepSeek V4.1 Flash (Reasoning, Max Effort) for stronger benchmark performance, and DeepSeek V4.1 Flash (Reasoning, Max Effort) for faster generation. For latency-sensitive apps, check the TTFT comparison above.