MiniMax M3 vs Claude (Sonnet 5, Sonnet 4.6, Opus 5): Where the 10x Premium Is Worth It

M3 costs $0.30 per million input tokens. Sonnet 5 costs $2, Sonnet 4.6 costs $3, Opus 5 costs $5. This page is only about one question: which tasks justify paying Anthropic ten times more, and which ones don't.

We ran both models on the same support agent for a week. Same system prompt. Same tool definitions. Same customer emails.

MiniMax M3 classified 94% of tickets correctly. Claude Sonnet 4.6 classified 97%.

M3 cost $18 for the week. Sonnet cost $89.

Is that 3% accuracy gap worth $71?

For a low-stakes email triage agent, no. For a healthcare intake agent where misclassification has consequences, absolutely. That's the entire question in one scenario. It isn't which model is better. It's whether the quality premium justifies the cost premium for your agent.

Here's the full breakdown.

The verdict (don't make me scroll for it)

MiniMax M3 is the better choice for high-volume, cost-sensitive agents handling structured tasks, long documents, or multimodal input including video. It's roughly 10x cheaper on input than Sonnet 4.6 and delivers strong performance on coding, browsing, and sustained agentic workflows.

Claude is the better choice for agents that need precise instruction following, reliable tool calling, nuanced reasoning, or customer-facing output quality. It costs more and justifies it on the tasks where getting it right matters more than getting it cheap.

One line per Claude model, since the answer changes depending on which one you're comparing:

• M3 vs Sonnet 5. Sonnet 5 wins on tool chains, conditional instructions and customer-facing output. M3 wins on cost (7x on input, 8x on output), video, and long-context bulk work. Route roughly 65% M3, 35% Sonnet 5.
• M3 vs Sonnet 4.6. Same verdict as Sonnet 5, but there's no reason to pick 4.6 over 5 in a new build. It costs more and scores lower.
• M3 vs Opus 5. Opus is about 17x M3's input price. Use it only for the reasoning-heavy slice: contracts, compliance, complex planning. Routing 35% of the work to Opus costs about $202 a month at 500 tasks a day, against $525 for all-Opus.

The smart play: M3 as your default for volume work, Claude for precision work. Route between them based on the task.

What changed in October 2026

The five-task test results further down are dated history and stay as they were. The price list has moved. Every price here was checked on 13 October 2026 on the provider's own pricing page.

• Claude Sonnet 5.5 is now the newest Sonnet. $2/$10 per million tokens, cache hits $0.10, batch $1/$5, 1M context. Same headline price as Sonnet 5, with cache hits at half Sonnet 5's $0.20. Sonnet 5 stays on sale at $2/$10 as a legacy model.
• Sonnet 4.6 is still on sale at $3/$15, but it is no longer the newest or the cheapest Sonnet. Against M3's $0.30/$1.20, the Sonnet 5.5 gap is the same as the Sonnet 5 gap: about 7x on input and 8x on output.
• Claude Haiku 5.5 (7 October) undercuts M3 on list price. $0.10/$0.50 with $0.01 cache hits for prompts up to 100K tokens. A prompt over 100K bills the whole request at $0.50/$2.50, which is above M3's sub-512K rate. Anthropic says the newer tokenizer produces roughly 30% more tokens for the same text than older models, so compare real bills, not rate cards. M3 still has the larger guaranteed window at its base rate and takes video input.
• Claude Opus 5.5 is unchanged at $4/$20 and is still the current Opus.
• Outside Anthropic, two more models now sit at or under M3's price. GLM-5.3 Flash is $0.15/$0.50 (GLM-5.3 itself is $1.40/$4.40). DeepSeek V4.1 Flash is $0.30/$1.20 at peak, the same as M3, and half that ($0.15/$0.60) off-peak. At the top end, GPT-6.1 Sol lists at $2/$10, the same as Sonnet 5.5.

None of the new models went through the five tests on this page, so there are no benchmark claims for them here.

Which Claude are we talking about?

Anthropic ships a lot of models at a lot of prices, and "is M3 better than Claude" has a different answer for each one. Every rate here is first-party, checked 13 October 2026, per million tokens.

Two things worth pulling out of that table. First, the whole Opus 4.x line costs exactly what Opus 5 costs, so there is never a price reason to run 4.6, 4.7 or 4.8. Second, Opus 5.5 arrived at $4/$20, which makes the current flagship 20% cheaper than the one it replaced. If you read an older comparison quoting $5/$25 as the Opus price, that's now the second-newest tier.

Everything in this post that says "Claude" applies to all of them. Where a specific model matters, we name it.

MiniMax M3 at a glance

Price: the numbers, corrected

Every rate below is first-party, checked 13 October 2026, per million tokens.

Two corrections that change the whole comparison.

First, M3's standard rate is $0.30/$1.20, not $0.60/$2.40. MiniMax publishes $0.30/$1.20 for any request with 512K or fewer input tokens. The $0.60/$2.40 rate is the tier a single request enters above 512K, and the entire call rebills at the higher rate. It is not a promo that expires. If you've read that M3 is "5x cheaper than Sonnet," that page used the wrong tier. The real gap under 512K is 10x on input against Sonnet 4.6 and 12.5x on output.

Second, Anthropic has a batch tier and MiniMax doesn't. For anything that isn't latency-sensitive, Sonnet 5 drops to $1/$5. That is a 50% cut on the Claude side of every table below, available by changing an API call.

What it costs in practice. An agent doing 500 tasks a day at 8K input and 2K output per task:

The Haiku 5.5 row uses the same token counts as the others. Anthropic's newer tokenizer produces roughly 30% more tokens for the same text, so its real bill will run somewhat higher.

At 100 tasks a day, divide by five: M3 $14, Sonnet 5 $108, Sonnet 4.6 $162. At 1,000 tasks a day, double it: M3 $144, Sonnet 5 $1,080, Sonnet 4.6 $1,620.

With prompt caching, Claude narrows the input gap. A cache hit is 10% of base input, so Sonnet 5's $2 becomes $0.20, which is cheaper than M3's uncached $0.30. But output is never cached, and Sonnet 5's $10 output against M3's $1.20 is where the money actually lives. For output-heavy agents that write reports, emails and summaries, M3 wins decisively no matter how good your caching is. For input-heavy agents re-reading the same long system prompt, the gap can shrink to almost nothing.

For the full per-day tables across five models, our agent cost breakdown does the arithmetic at 100, 500 and 2,000 tasks a day.

Context window: closer than you've been told

MiniMax M3: 1M ceiling, 512K guaranteed minimum, and that maximum counts input and output combined. Independent trackers list usable context as 512K for exactly that reason. Cross 512K and the whole request doubles in price.

Claude Sonnet 4.6, Sonnet 5, Opus 5: 1M tokens, billed at standard rates across the full window. Anthropic's pricing page is explicit: Claude 4.6 and later include the full 1M context window at standard pricing, so a 900K-token request costs the same per token as a 9K one.

This is a reversal from what most comparisons still say. Sonnet 4.6 stopped being a 200K model in March 2026. There is no "M3 has 5x the context" advantage any more. Both are 1M-class, and M3's is the one with an asterisk on it, because its window is a ceiling over a guaranteed floor with a billing step in the middle.

What M3 does still own is the price of long context. Under 512K it is the cheapest million-token-class inference available anywhere. Above it, still cheap, just less dramatically so.

The practical advice for either model: prune between turns. Agent loops append tool results and reasoning every turn, so by turn fifteen you're carrying history no single step needs, and on M3 that's what pushes you over the cliff.

Speed

MiniMax M3 is built for long-horizon work. MSA processes long contexts efficiently and the model sustains autonomous runs over hours. On MiniMax's own API it measures around 106 output tokens per second, and third-party hosts vary enormously, from roughly 18 tokens per second at the slow end to over 400 at the fast end. Check your provider rather than the model.

Sonnet 4.6 runs roughly 50-80 tok/s depending on provider and load. Opus 5 is slower still in standard mode, with a research-preview Fast mode at $10/$50 for latency-sensitive work.

For real-time chat agents the difference is noticeable. For scheduled background agents it is irrelevant, and you should be using Anthropic's batch tier anyway.

Head-to-head on 5 real agent tasks

Task 1: Summarization

Feed both models a 50,000-token document and ask for a 500-word executive summary.

M3 wins on cost, ties on quality. Both hold 50K comfortably. M3 does it at a tenth of the price and summary quality is comparable for factual content. Where Claude pulls ahead is judgment about what matters: M3 occasionally promotes a minor detail into a "key" takeaway. For internal briefings that's fine. For a summary going to a client or an executive, use Claude.

Task 2: Coding

Both are strong. M3 scores 80.5% on SWE-bench Verified and 59.0% on SWE-bench Pro. Sonnet 4.6 is competitive; Sonnet 5 has since posted 63.2% on SWE-bench Pro and 85.2% on SWE-bench Verified, which puts the current Anthropic mid-tier clearly ahead of M3 on published coding scores rather than merely adjacent.

M3 still wins on sustained coding sessions, because it's designed for multi-hour autonomous runs. Claude is better for short, precise code edits where instruction following matters more than endurance, and for anything where the code ships without review. For the three-way read against the open-weight GLM family, see our GLM 5.2 vs Sonnet 4.6 vs MiniMax M3 benchmark comparison.

Task 3: Tool calling

This is where Claude pulls ahead, and it is the single most expensive difference between these models.

We ran a four-tool chain: read a ticket, look up the customer in CRM, check subscription tier, search the knowledge base, draft a tier-appropriate response.

• Claude: 97% correct end-to-end. Handled ambiguous customer data cleanly. Draft quality customer-ready.
• M3: 90% correct end-to-end. Occasional wrong tool parameter on ambiguous inputs. Drafts needed light editing.

M3 supports tool calling and scores well on agentic benchmarks (BrowseComp 83.5), but on complex chains where one wrong call cascades into a workflow failure, Claude picks the right tool and formats the right arguments more consistently. That 7-point end-to-end gap is the whole story, and it compounds with chain length: a task needing four correct calls in a row punishes a per-call error rate four times over.

Claude wins. The maths is in the routing section below, and it is not close.

Task 4: Long context processing

Both are 1M-class, so this is no longer a walkover for M3. Under 512K, M3 does it for a tenth of the price and MSA keeps performance stable. Above 512K, M3 doubles and the latency variance widens.

Claude maintains higher attention quality across long contexts. The lost-in-the-middle effect hits both, but Claude degrades more gracefully: on MRCR v2 at 1M context, Opus measures around 76% against an estimated 60-65% for M3.

Verdict: M3 for bulk long-context work under 512K. Claude for documents over 50K tokens where precision actually matters.

Task 5: Customer-facing responses

Feed both a customer complaint and ask for a response matching a brand voice guide.

Claude wins. Anthropic's instruction following produces more natural, empathetic, brand-consistent output. Tell Claude "never mention competitor products" and it follows. Tell it "always use formal tone except when the customer uses informal language" and it handles the conditional. M3's responses are competent but less nuanced on tone calibration, and it follows complex conditional rules less consistently.

Where the Claude premium is wasted

Email classification. 100 emails, five categories, structured JSON out. M3: 94-96% accuracy. Claude: 97-98%. A human reviews the borderline cases either way. Use M3.

Data extraction. Vendor name, amount, date and category from 50 receipt emails. M3: 93% field-level accuracy, with occasional MM/DD versus DD/MM confusion. Claude: 96%, better on ambiguous date formats. For internal expense tracking where a human reviews the spreadsheet, that gap doesn't justify 10x. Use M3.

Browsing and research. M3 scored 83.5 on BrowseComp, ahead of Opus 4.7's 79.3 on browsing tasks, and it's faster. Use M3.

Bulk summarisation for internal use. Covered above. Use M3.

For structured tasks with clear inputs and expected outputs, M3 matches or nearly matches Claude at 7-17x less cost. Paying the premium here is just paying the premium.

Where the Claude premium earns its price

Complex multi-step tool chains. Here is the arithmetic that settles it. At 500 daily tickets, M3's 90% end-to-end rate produces about 50 failures a day; Claude's 97% produces about 15. Those 35 extra failures need human review at roughly five minutes each, so 175 minutes, nearly three hours. At $30/hour that's $87.50/day in review labour. The extra model cost of running those 500 tasks on Sonnet 5 instead of M3 is $15.60/day. The premium pays for itself more than five times over.

Legal and compliance work. We ran both on a 50-page NDA from an actual partnership deal. M3 caught 4 of 6 non-standard clauses. Claude caught all 6, including a carve-out in the indemnification section that would have limited our liability cap. Our lawyer's note: "better than what most junior associates produce." Missing an indemnification clause costs more than the entire year's API budget.

Customer-facing output that ships unedited. M3 is functional, correct and generic. Claude is polished and brand-consistent. If a human polishes before sending, use M3. If it goes straight out, don't.

Anything with conditional instruction-following. Multi-clause rules, exceptions, escalation conditions. Claude handles the conditionals. M3 handles them most of the time, which is a different thing.

The decision framework (one question)

Ask: what does a wrong answer on this task cost?

• Wrong classification on an internal email? $0. Use M3.
• Wrong extraction on an expense receipt a human reviews anyway? $0. Use M3.
• Wrong tool call on a customer support ticket? Five minutes of a $30/hour reviewer. Use Claude.
• A clause missed in a contract? Five figures of legal exposure. Use Claude.
• Wrong tone in a customer email? Churn risk. Use Claude.

The break-even sits around $0.05: if a wrong answer costs more than that in downstream consequences, Claude pays for itself. If it costs nothing, M3 is pure savings.

The routing math

The builders getting the best results don't pick one. They run M3 on the 65% of tasks where wrong answers are cheap and Claude on the 35% where they aren't.

At 500 tasks a day with a 3K input / 800 output profile:

• All M3: $0.93/day, $28/month
• All Sonnet 5: $7.00/day, $210/month
• All Opus 5: $17.50/day, $525/month
• Routed, 65% M3 / 35% Opus 5: $0.60 + $6.13 = $6.73/day, $202/month
• Routed, 65% M3 / 35% Sonnet 5: $0.60 + $2.45 = $3.05/day, $92/month

Routing 35% of the work to Opus 5 costs $202/month against $525 for all-Opus. You keep flagship reasoning on the tasks that need it and pay 62% less for the privilege. Route to Sonnet 5 instead and you're at $92/month, less than a fifth of the all-Opus bill, with tool-chain accuracy that's still dramatically better than M3's on the hard 35%.

The all-M3 column looks like the winner until you price the 250 tool-call failures a day it comes with.

On BetterClaw you can connect both MiniMax and Anthropic keys to the same agent and set a per-agent monthly cap. The agent defaults to M3, escalates to Claude when task complexity warrants it, and pauses with an alert instead of running up the bill if it hits the cap. 28+ providers via BYOK, zero inference markup. Free plan with 1 agent and 100 credits a month. Pro is $49/month for 5 agents, $39 on annual.

Can I use MiniMax M3 in Claude Code?

Yes. MiniMax runs an Anthropic-compatible endpoint, so Claude Code can point at M3 with a few settings in ~/.claude/settings.json:

{
  "env": {
    "ANTHROPIC_BASE_URL": "https://api.minimax.io/anthropic",
    "ANTHROPIC_AUTH_TOKEN": "your-minimax-api-key",
    "ANTHROPIC_MODEL": "MiniMax-M3[1m]",
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "MiniMax-M3[1m]",
    "ANTHROPIC_DEFAULT_OPUS_MODEL": "MiniMax-M3[1m]",
    "ANTHROPIC_DEFAULT_HAIKU_MODEL": "MiniMax-M3[1m]",
    "CLAUDE_CODE_AUTO_COMPACT_WINDOW": "1000000"
  }
}

Two things to know. First, the [1m] suffix and the compact window setting matter: without them Claude Code may treat M3 as a 200K model and compact early. Second, M3 uses interleaved thinking between tool calls, and it works best when that reasoning is kept in the conversation, which Claude Code does. Verify the endpoint and model name against MiniMax's own docs before you rely on it, because they change.

Is it a good idea? For long autonomous coding sessions where cost matters, yes, and it's the cheapest 1M-context model you can put in Claude Code. For short, precise edits that ship without review, Sonnet 5 is still the safer default. Same routing logic as the rest of this post.

Who should use which

Use MiniMax M3 when:

Budget is a factor and you're processing high volume. At $0.30/M against $2-5/M, savings compound fast across thousands of daily tasks.

Your agent handles long documents or extended research sessions and you can keep single requests under 512K.

You need multimodal, especially video. M3 processes text, image and video; Claude handles text and image but not video.

You want open weights. Note the licence, though: M3 is not MIT. It ships under the MiniMax Community License, which requires "Built with MiniMax M3" attribution, a one-time notice to MiniMax, and prior written authorisation above roughly $20M in annual product revenue. Plenty of pages call it MIT. They're wrong.

Use Claude when:

Tool-calling reliability is critical. 97% end-to-end against M3's 90% on our four-tool chain means far fewer production failures on multi-tool workflows.

Customer-facing output quality matters, meaning tone, empathy and brand voice consistency.

You want the batch tier, prompt caching, extended thinking or the broadest MCP support.

The task involves nuanced judgment rather than execution: complex reasoning, conditional logic, ambiguous instructions.

And pick the right Claude. Sonnet 5 at $2/$10 is both cheaper than Sonnet 4.6 at $3/$15 and stronger on every published coding benchmark (85.2% SWE-bench Verified, 63.2% SWE-bench Pro, 80.4% Terminal-Bench 2.1). There is no good reason to start a new agent on 4.6. Reserve the Opus tier for the reasoning-heavy top slice, and prefer Opus 5.5 at $4/$20 over Opus 5 at $5/$25 now that it exists.

The teams building the best agents in 2026 use both sides of this table. They route. They match the model to the task. They don't overpay on email triage and they don't underspend on customer communication.

Give BetterClaw a look if you want both available from one dashboard. Free plan with 1 agent and 100 credits a month. Pro is $49/month for 5 agents. We handle the model routing. You handle the agent logic.

Frequently Asked Questions

What is MiniMax M3?

MiniMax M3 is a 428B-parameter open-weight mixture-of-experts model from MiniMax, with about 23B parameters active per token, released on 1 June 2026. It has a 1M-token context ceiling (512K guaranteed, input and output combined), accepts text, image and video input, outputs text, and costs $0.30 per million input tokens and $1.20 per million output tokens up to 512K input. Published scores include 80.5 on SWE-bench Verified, 59.0 on SWE-bench Pro, 66.0 on Terminal-Bench 2.1 and 83.5 on BrowseComp. It ships under the MiniMax Community License rather than MIT.

Is MiniMax M3 better than Claude Sonnet 5?

Not overall. Sonnet 5 is ahead on published coding benchmarks (85.2 against 80.5 on SWE-bench Verified) and ahead in our own tests on tool chains and customer-facing writing. M3 is ahead on cost, video input and browsing (BrowseComp 83.5). Use M3 for volume, Sonnet 5 for precision, and route between them rather than picking one.

MiniMax M3 vs Claude Opus 4.6: which should I use?

Opus 4.6, 4.7, 4.8 and 5 all cost $5/$25 per million tokens, so there is no price reason to run an older one. Opus 5.5 is now the current flagship at $4/$20, which makes it both newer and cheaper than all of them. Against M3, the Opus tier costs roughly 13 to 17x more on input. It earns that on legal, compliance and complex planning work and nowhere else.

How does MiniMax M3 compare to Claude Sonnet 4.6 for AI agents?

M3 is 10x cheaper on input ($0.30/M against $3/M) and 12.5x cheaper on output ($1.20 against $15) for requests up to 512K input tokens. Both are now 1M-context-class, since Sonnet 4.6 has billed its full 1M window at standard rates since March 2026, so the old "M3 has 5x the context" claim no longer holds. In our four-tool chain test Claude finished 97% of chains correctly against M3's 90%, and it follows conditional instructions and brand voice more reliably. M3 wins on volume, cost and video input. Most production setups use both with task-based routing, and new builds should use Sonnet 5 rather than 4.6.

Can I use MiniMax M3 with Claude Code?

Yes, through MiniMax's Anthropic-compatible endpoint. Point ANTHROPIC_BASE_URL at https://api.minimax.io/anthropic in ~/.claude/settings.json, set ANTHROPIC_AUTH_TOKEN to your MiniMax key, and set the model keys to MiniMax-M3[1m] with CLAUDE_CODE_AUTO_COMPACT_WINDOW at 1000000 so Claude Code doesn't treat M3 as a 200K model and compact early. It's the cheapest 1M-context model you can run in Claude Code, and it suits long autonomous sessions. For short edits that ship without review, Sonnet 5 remains the safer default.

How fast is MiniMax M3?

About 106 output tokens a second on MiniMax's own API, which puts it ahead of Sonnet 4.6's 50 to 80 tok/s. Third-party hosts vary hugely, from under 20 tokens a second to over 400, so the provider matters more than the model. Its real advantage is at long context, where MSA cuts per-token compute to roughly a twentieth of the previous generation.

Is MiniMax M3 reliable enough for production agents?

Yes, with the right task match. It scored 59.0% on SWE-bench Pro and 83.5 on BrowseComp, and it handles structured extraction, summarisation, coding and browsing reliably. For multi-tool chains where one wrong call cascades, Claude's 97% end-to-end accuracy against M3's 90% makes it the safer choice. Use M3 for volume work and Claude for high-stakes tool chains.

How much can I save switching from Claude to MiniMax M3?

For an agent at 500 tasks/day with 8K input and 2K output per task: Sonnet 4.6 costs about $810/month, Sonnet 5 about $540, M3 about $72. Savings scale linearly with volume. The catch is that you should only switch the tasks where M3 matches quality, meaning summarisation, extraction, classification, browsing and bulk long-context work, and keep Claude for customer communication, complex tool chains and anything safety-critical. On tool chains the review labour from M3's extra failures ($87.50/day at 500 tickets) costs far more than the $15.60/day the model swap saves.

Is MiniMax M3 Apache or MIT licensed?

Neither. M3 ships under the MiniMax Community License: open weights, but with commercial conditions. You must display "Built with MiniMax M3" on your product or documentation, send MiniMax a one-time notice, and obtain prior written authorisation if the product generates more than roughly $20M in annual revenue. MiniMax has said directly that it should not be described as a modified MIT licence. If you need unrestricted open weights, GLM's models are MIT.

Should I use Claude Sonnet 4.6 or Sonnet 5?

Sonnet 5, unless you have a specific reason not to. It costs $2/$10 per million tokens against Sonnet 4.6's $3/$15, and it scores higher on every published coding benchmark. Anthropic confirmed the $2/$10 launch rate is now the standard price rather than introductory. One thing to watch: Claude 4.7 and later use a newer tokenizer that produces roughly 30% more tokens for the same text, so the bill does not drop by the full third the rate card implies.

Does MiniMax M3 support video and image input?

Yes. M3 natively processes text, images and video in the same model. Claude supports text and images but not video. If your agent analyses video content, such as product demos, meeting recordings or visual inspections, M3 is the option in this price range. For text-only or text-plus-image agents, both work well.