MiniMax M3.1 Flash vs DeepSeek V4.1 Flash vs Claude Haiku 5.5: One Bug Fix, Three Bills

Three cheap coding models shipped within four weeks of each other: DeepSeek V4.1 Flash (with its 1017 update), Claude Haiku 5.5, and MiniMax M3.1 Flash, which spent its first week as the anonymous Space Bunny. All three have a 1M-token context window and cost between $0.10 and $0.17 per million input tokens. So which one should you use for routine coding?

AIHubMix gave all three the same bug fix, three times each, through one API key. Each model fixed the bug correctly every time, but the bills and wait times differed a lot:

• Claude Haiku 5.5 was the fastest and cheapest at its default settings: about 7 seconds and $0.0007 per fix.
• DeepSeek V4.1 Flash 1017 took about 15 seconds and $0.0014.
• MiniMax M3.1 Flash at its default took 56 seconds and $0.0045. Set to low, it dropped to 9.5 seconds and $0.0006, the cheapest result in the test.

The task doesn't pick a winner on correctness. Below is what each model costs on it, and where each one is the right choice.

Why these three

They compete for the same job. All three are the cheap, fast tier of their vendor's line-up, aimed at everyday coding and agent steps:

• DeepSeek released V4.1 Flash on 10 September and the 1017 update on 17 October.
• Anthropic released Haiku 5.5 on 7 October.
• MiniMax's model appeared as Space Bunny Alpha on 23 September, got its name on 27 September, and became callable per token on AIHubMix on 19 October.

Users already compare them. During Space Bunny's free week on OpenRouter, it topped the daily chart, ahead of DeepSeek V4.1 Flash. OrcaRouter published a Haiku 5.5 vs M3.1 Flash comparison the day after Haiku launched.

Prices are AIHubMix list prices on 19 October 2026. AIHubMix is running a 30% discount on DeepSeek V4.1 Flash 1017 from 19 to 25 October, not included above. Haiku 5.5 costs $0.50 / $2.50 for prompts over 100K tokens, five times the base rate. DeepSeek's own API charges double at peak hours, while AIHubMix lists one price. Video input for M3.1 Flash is in MiniMax's docs; AIHubMix currently lists text and image for it.

The specs come from each vendor's docs: MiniMax's model list, DeepSeek's models and pricing page, and Anthropic's Haiku page. DeepSeek's benchmark scores are self-reported in its V4.1 Flash technical report. Haiku's Artificial Analysis score of 43 is cited by OrcaRouter. M3.1 Flash has no published benchmark from MiniMax or anyone else.

The task

The test is a two-bug fix in a billing function, the kind of "quick bug fix" all three vendors advertise these models for:

def billable_days(start: date, end: date, pauses: list[tuple[date, date]]) -> int:
    """Days in the half-open period [start, end) when the subscription was active.
    `pauses` holds inclusive (first_day, last_day) ranges..."""
    total = (end - start).days
    for p_start, p_end in pauses:
        s = max(p_start, start)
        e = min(p_end, end)
        if s <= e:
            total -= (e - s).days + 1
    return total

The prompt names the symptoms ("charged for one day less" when a pause runs past the period end, and "too few days, sometimes negative" with overlapping pauses) and asks for the corrected function only. A local harness then runs 215 hidden cases against it: 15 hand-written edge cases (touching pauses, nested pauses, a pause covering the whole period, an empty period) and 200 random ones checked against a brute-force reference. The original function passes 138 of them.

Each model ran three times through AIHubMix's Chat Completions endpoint on 19 October 2026, at its default settings. M3.1 Flash also ran at low. All figures were measured by AIHubMix; nobody else has reproduced them.

Results

Costs use each model's AIHubMix price for input, cached input, and output. Thinking tokens are billed as output on all three.

Here is what the results show:

• Correctness tied. Twelve runs, twelve perfect fixes. This task can't separate the three models on quality, and we won't pretend it does.
• The default settings decide the bill. Flash's default thinks about 8× as much as Haiku's on the same fix. Haiku's default fix costs about a sixth of Flash's default ($0.70 vs $4.45 per thousand fixes).
• Flash at low is the cheapest configuration, at $0.64 per thousand fixes, slightly under Haiku's $0.70. Haiku is still faster.
• Raw speed differs as well. Output tokens divided by wall time came to about 183 tokens/s for Haiku, 148 for DeepSeek, and 112 for Flash. Haiku produces fewer tokens and produces them faster.

Per 1,000 fixes like this one: Haiku about $0.70, DeepSeek about $1.35, Flash about $4.45 at default or $0.64 at low.

On a second, much shorter task, sorting five support tickets into four labels, all 30 answers were correct across the three models and their settings. Every call cost under $0.0001. Flash used 0 to 6 thinking tokens, Haiku used none, and DeepSeek used about 25, even with reasoning_effort: "none" sent through AIHubMix. On short calls like these, none of the differences matters to the bill.

Where each one wins

Claude Haiku 5.5 is the default choice when a person is waiting. It was the fastest and cheapest at default settings, and it has the strongest independent score of the three. It's weaker in two places: the price jumps fivefold once a prompt passes 100K tokens, and output caps at 128K.

DeepSeek V4.1 Flash 1017 is the choice when you need evidence and control. It has the most published benchmark data, open weights under MIT, a real non-thinking mode, and 384K of output. Its default thinking on our task sat between the other two.

MiniMax M3.1 Flash is the choice for long inputs at a flat price, or when you'll tune effort. AIHubMix lists one price regardless of prompt length, output goes up to 512K, and MiniMax documents video input. At low it was the cheapest model in the test. It's weaker in three places: its default is the slowest and most expensive setting here, nobody has benchmarked it yet, and thinking can't be turned off.

The long-prompt difference is easy to underestimate. As an estimate, take a 300K-token codebase prompt with no caching and count input cost only. Assuming Haiku 5.5 applies its over-100K rate to the whole prompt, as OrcaRouter describes it, the input costs 300,000 × $0.50 ÷ 1M = $0.15. M3.1 Flash costs 300,000 × $0.165 ÷ 1M ≈ $0.05, and DeepSeek about the same. That makes Haiku roughly 3× the price per call.

Who should pick which

• Interactive coding help, short prompts, people waiting: Claude Haiku 5.5.
• Pipelines that need benchmarks, self-hosting, or calls that skip thinking entirely: DeepSeek V4.1 Flash 1017.
• Large-context work, long generated outputs, or video input, with effort set explicitly: MiniMax M3.1 Flash at low or medium.
• Not sure: run your own task on all three. It takes one key and one loop.

Run all three with one key

On AIHubMix, all three answer on the same OpenAI-compatible endpoint, so only the model ID changes. The quick start covers the key:

import os, time
from openai import OpenAI

client = OpenAI(base_url="https://aihubmix.com/v1", api_key=os.environ["AIHUBMIX_API_KEY"])
prompt = open("task.md").read()

for model, extra in [("minimax-m3.1-flash", {"reasoning_effort": "low"}),
                     ("deepseek-v4.1-flash-1017", {}),
                     ("claude-haiku-5-5", {})]:
    t0 = time.time()
    r = client.chat.completions.create(model=model, max_tokens=32768,
                                       messages=[{"role": "user", "content": prompt}], **extra)
    print(model, round(time.time() - t0, 1), "s", r.usage.completion_tokens, "output tokens")

The side-by-side price cards are on AIHubMix's compare pages: M3.1 Flash vs DeepSeek V4.1 Flash 1017 and M3.1 Flash vs Claude Haiku 5.5.

FAQ

Which is better for coding: MiniMax M3.1 Flash, DeepSeek V4.1 Flash, or Claude Haiku 5.5?
On our two-bug fix, all three were correct every time. Haiku 5.5 was the fastest and cheapest at default settings, and M3.1 Flash was the cheapest once set to low effort. DeepSeek has the most published benchmark data.

Why was MiniMax M3.1 Flash so slow in the test?
Its default thinking level is max. On the same fix it used about 6,400 thinking tokens at default and about 600 at low, and the time fell from 56 to under 10 seconds.

Is DeepSeek V4.1 Flash 1017 different from DeepSeek V4.1 Flash?
1017 is DeepSeek's 17 October 2026 update to V4.1 Flash, with the same 1M context and 384K output limit. On AIHubMix it is deepseek-v4.1-flash-1017.

Which model is cheapest for long prompts?
For prompts over 100K tokens, MiniMax M3.1 Flash and DeepSeek V4.1 Flash cost about a third of Claude Haiku 5.5, because Haiku's rate rises fivefold above 100K.

Can all three be called with one API key?
Yes. On AIHubMix all three use the same key and the same OpenAI-compatible endpoint; only the model ID changes.

Does MiniMax M3.1 Flash have benchmark scores?
Not yet. MiniMax hasn't published any, and it isn't on Artificial Analysis. Tables that show scores for it are usually showing MiniMax M3's.

Keep reading: the MiniMax M3.1 Flash series

• If Flash made your shortlist, start with what it is and what it replaced, from Space Bunny to its price against M2.7 and M3: MiniMax M3.1 Flash Is Space Bunny: What Changed from M2.7 and M3, and What It Costs
• Flash's result here depends almost entirely on one setting. This post measures all five levels: MiniMax M3.1 Flash Effort Levels: Why the Default Cost 7× Low on the Same Bug Fix
• If you're moving existing MiniMax M2.5/M2.7 code rather than starting fresh, read the errors and silent changes first: Moving Off MiniMax M2.5/M2.7 Before Nov 18: Fixing M3.1 Flash's "requires adaptive thinking" 400

Sources

• MiniMax: Models
• DeepSeek: Models & Pricing
• Anthropic: Claude Haiku
• AIHubMix: MiniMax M3.1 Flash vs DeepSeek V4.1 Flash 1017
• OrcaRouter: Claude Haiku 5.5 vs MiniMax M3.1 Flash Preview