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GPT-5.6 Sol vs MiniMax M3

MiniMax M3 has been retired from our catalogue. Its figures below are the last published rates; calls to it are no longer served, while the other model in this comparison is.

vs

Which one, when

Both take text and image in and return text, both can turn thinking off, and their context windows are close at 1050000 tokens for gpt-5.6-sol versus 1000000 for minimax-m3, so the real split is price and output shape. minimax-m3 costs about 16.7x less on input and 25x less on output ($0.3/$1.2 per million versus $5/$30), also accepts video, and can emit up to 524288 tokens against 128000 - pick it for high-volume, long-output, long-context work. Choose gpt-5.6-sol when you want OpenAI's July 2026 generation with an explicit vision capability flag and a 2026-02 knowledge cutoff.

Benchmarks

MiniMax M3: the vendor has not published benchmark scores.

Above averageNo peer higherGPT-5.6 Sol94 / 12128 / 121
GPT-5.6 Sol MiniMax M3 other models measured peer average ★ no peer scored higher
SWE-Bench Pro
64.6%
N/A
BioMysteryBench hard
44.7%
N/A
OSWorld-Verified
83%
N/A
Cybergym
84.5%
N/A
HealthBench Professional
60.5%
N/A
Finance Agent v2
53.8%
N/A
Harvey Lab-AA
87.2%
N/A
GPQA Diamond
94.6%
N/A
BrowseComp
90.4%
N/A
LVBench
82.1%
N/A

Vendor-published: Alibaba (Qwen) Anthropic ByteDance DeepSeek Google MiniMax Moonshot OpenAI Tencent Z.ai

Pricing

GPT-5.6 Sol MiniMax M3 Δ
Input / 1M tokens $5 $0.3 17×
Output / 1M tokens $30 $1.2 25×
Cache read / 1M tokens $0.5 $0.06 8.3×
Cache write no separate charge no separate charge -

Rates from the live catalogue at build time; each model page carries the current rate card.

Where they sit · input price per 1M tokens across all 76 chat models on this billing unit (log scale)

GPT-5.6 Sol · $5 MiniMax M3 · $0.3
$0.05 · Qwen3 VL Flash $30 · GPT-5.4 Pro

Capabilities

GPT-5.6 Sol MiniMax M3
Tool calling yes yes
Thinking control configurable configurable
Structured output yes -
Prompt caching implicit (automatic) implicit (automatic)
Cache lifetime 5-10m, up to 1h not published
Minimum cached prefix 1024 tokens 512 tokens

Specs

GPT-5.6 Sol MiniMax M3
Input modalities text image text image video
Output modalities text text
Released 2026-07-09 2026-06-01
Knowledge cutoff 2026-02 -
Context window 1.1M 1M
Max output 128K 524K
Thinking parameter reasoning.effort
  • thinking.type
  • reasoning_split
Accepted values
reasoning.effort
  • none
  • low
  • medium
  • high
  • xhigh
  • max
thinking.type
  • adaptive
  • disabled
reasoning_split
  • boolean
Default medium adaptive: thinking on, with the model deciding when extra reasoning helps

Specs are transcribed from each vendor’s documentation; a row a vendor does not publish is left out rather than inferred. Full sources: GPT-5.6 Sol · MiniMax M3

Switch between them with one line

Both ids are in every tab below; the highlighted pair of lines is the only edit. Same endpoint, same key, same request shape.

from openai import OpenAI

client = OpenAI(
    base_url="https://synthorai.io/v1",
    api_key="sk-syn-...",
)

resp = client.chat.completions.create(
    model="gpt-5.6-sol",
    # model="minimax-m3",  # uncomment this line, comment the one above
    messages=[{"role": "user", "content": "Summarize this diff"}],
    reasoning_effort="medium",
)
print(resp.choices[0].message.content)

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FAQ

Which is cheaper, GPT-5.6 Sol or MiniMax M3?

MiniMax M3 is cheaper on the "Input / 1M tokens" row ($0.3 vs $5, 17× apart). Other rows may point the other way; the table above carries the full rate card, and real cost depends on your mix.

Can I A/B test GPT-5.6 Sol against MiniMax M3 without two integrations?

Yes. Both are served through the same OpenAI-compatible endpoint with one API key. Switching is a one-line change to the model id, so you can route a fraction of traffic to each and compare bills directly.

Do GPT-5.6 Sol and MiniMax M3 support prompt caching?

Yes. Both bill cache reads below their input rate, so warm-prefix workloads cost less than the list rates suggest. The exact cache-read rows are in the pricing table above.

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