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Claude 3 Haiku vs MiniMax M3

Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

Claude 3 Haiku and MiniMax M3 are priced within ~10% of each other.

Claude 3 Haiku does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

anthropic

Claude 3 Haiku

Blended / 1M
$0.500
Context
200K
Released
Mar 13, 2024
Overall score
Not evaluated
tool callingimage inputprompt caching

minimax

MiniMax M3

Blended / 1M
$0.525
Context
1.0M
Released
May 31, 2026
Overall score
67.3
reasoningtool callingimage inputvideo inputprompt caching

Specs and pricing

MetricClaude 3 HaikuMiniMax M3
LiveBench overall

Mean of the seven LiveBench category scores, 0–100. Higher is better.

67.3
Cost per point

Measured benchmark spend divided by overall score — dollars per point of capability.

$0.0339
Blended price / 1M

3:1 input:output mix, the usual shape of production traffic.

$0.500$0.525
Input price / 1M$0.250win$0.300
Output price / 1M$1.25$1.20
Cached input / 1M

Price of an input token served from the prompt cache, where the provider publishes one.

$0.030win$0.060
Context window200K1.0Mwin
Max output tokens4K512Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Claude 3 Haiku on top, MiniMax M3 below, both out of 100.

Agentic coding
40.7
Coding
68.2
Reasoning
74.5
Mathematics
76.9
Data analysis
76.2
Language
76.8
Instruction following
57.5

What each one costs to run

Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.

WorkloadClaude 3 HaikuMiniMax M3
Support chatbot

1.2K in / 400 out × 200K requests

$144.16/mo$150.72/mo
RAG assistant

8K in / 600 out × 100K requests

$187.00/mo$216.00/mo
Coding agent

40K in / 4K out × 20K requests

$176.80/mo$201.60/mo
Document extraction

20K in / 1.5K out × 50K requests

$332.75/mo$378.00/mo
Bulk classification

500 in / 20 out × 5M requests

$640.00/mo$750.00/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

MiniMax M3

Wider context window — 1.0M against 200K.

Claude 3 Haiku vs MiniMax M3 FAQ

Which is better, Claude 3 Haiku or MiniMax M3?

Claude 3 Haiku and MiniMax M3 are priced within ~10% of each other. Claude 3 Haiku does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

Is Claude 3 Haiku cheaper than MiniMax M3?

They cost about the same. Both land near $0.500 per million tokens on a 3:1 input:output blend, so price is unlikely to be the deciding factor between them.

Does Claude 3 Haiku or MiniMax M3 have a bigger context window?

MiniMax M3 has the larger context window: 200K for Claude 3 Haiku against 1.0M for MiniMax M3. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.

Do Claude 3 Haiku and MiniMax M3 support prompt caching?

Both publish a cached-input rate: $0.030 per million for Claude 3 Haiku and $0.060 for MiniMax M3, against full input rates of $0.250 and $0.300. On a workload with a long stable prefix — a system prompt, a tool schema, a retrieved corpus — that changes the economics more than the headline price does.

Related comparisons

How these numbers are produced

  • Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
  • ScoresLiveBench release 2026-06-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
  • Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
  • “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.

Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.