Magnum v4 72B vs GPT-5.1-Codex-Max

Magnum v4 72B costs 2.0x less per output token than GPT-5.1-Codex-Max ($5.00 vs $10.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Replace Magnum v4 72B Replace GPT-5.1-Codex-Max

A Magnum v4 72BAnthracite

Coding: No data
Overall: No data
Output $/M: $5.00

GPT-5.1-Codex-MaxOpenAI

Coding: No data
Overall: No data
Output $/M: $10.00

vs $5.00 vs $10.00 per 1M output tokens. Magnum v4 72B is 2.0x cheaper.

Magnum v4 72B or GPT-5.1-Codex-Max: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Magnum v4 72B for output tokens 2.0x cheaper ($5.00 vs $10.00 per million).

Model AMagnum v4 72BAnthraciteNot benchmarkedNo coding benchmarkNo cost per solved task Model BGPT-5.1-Codex-MaxOpenAINot benchmarked1 independent benchmarkNo cost per solved task

No benchmark has tested both yet. Magnum v4 72B has none yet; GPT-5.1-Codex-Max on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench. Compare them on price and context instead.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Long documents
Listed context window
GPT-5.1-Codex-Max
GPT-5.1-Codex-Max takes 400K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Magnum v4 72B
Magnum v4 72B $0.0050, GPT-5.1-Codex-Max $0.0063 per turn.
List prices

At a glance

Coding index: Magnum v4 72B not benchmarked, GPT-5.1-Codex-Max not benchmarked.
Widest category: None yet: no category has been tested on both models.
Widest single gap: None yet: no benchmark has tested both models.
Output price: Magnum v4 72B $5.00 against GPT-5.1-Codex-Max $10.00 per million output tokens, 2.0x apart.
Context window: Magnum v4 72B takes 33K tokens, GPT-5.1-Codex-Max 400K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured

Coding benchmarks for Magnum v4 72B and GPT-5.1-Codex-Max
Benchmark	Magnum v4 72B	GPT-5.1-Codex-Max	Leader
LiveCodeBench (Vals AI)	Not measured	83.6%	Only GPT-5.1-Codex-Max measured
Vibe Code Bench (Vals AI)	Not measured	22.2%	Only GPT-5.1-Codex-Max measured
Terminal-Bench	Not measured	60.4%	Only GPT-5.1-Codex-Max measured
ALE-Bench	Not measured	1228.3	Only GPT-5.1-Codex-Max measured
Neither model has a result on the other 35 boards here

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured

Agentic work benchmarks for Magnum v4 72B and GPT-5.1-Codex-Max
Benchmark	Magnum v4 72B	GPT-5.1-Codex-Max	Leader
METR time horizons	Not measured	70.8%	Only GPT-5.1-Codex-Max measured
Neither model has a result on the other 40 boards here

MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured

Math benchmarks for Magnum v4 72B and GPT-5.1-Codex-Max
Benchmark	Magnum v4 72B	GPT-5.1-Codex-Max	Leader
ProofBench	Not measured	9.0%	Only GPT-5.1-Codex-Max measured
Neither model has a result on the other 12 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Magnum v4 72B$0.0050Fits in one request

GPT-5.1-Codex-Max$0.0063Fits in one request

Magnum v4 72B costs less

Repository review

50K input + 3K output tokens

Magnum v4 72B$0.140Exceeds the context window

GPT-5.1-Codex-Max$0.092Fits in one request

GPT-5.1-Codex-Max costs less

Agent loop

200K input + 10K output tokens

Magnum v4 72B$0.550Exceeds the context window

GPT-5.1-Codex-Max$0.350Fits in one request

GPT-5.1-Codex-Max costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Magnum v4 72B and GPT-5.1-Codex-Max
Specification	Magnum v4 72B	OpenAI GPT-5.1-Codex-Max
Maker	Anthracite	OpenAI
Weights	Open weights	No public weights listed
Released	October 22, 2024	December 4, 2025
Context window	33K	400K
Input $/Mtok	$2.50	$1.25
Output $/Mtok	$5.00	$10.00
Coding index	Not benchmarked	Not benchmarked
Independent measurements behind it	0	1
Cost per solved task	Not computable	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is Magnum v4 72B better than GPT-5.1-Codex-Max for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Magnum v4 72B for output tokens 2.0x cheaper ($5.00 vs $10.00 per million).

Which is cheaper, Magnum v4 72B or GPT-5.1-Codex-Max?

Magnum v4 72B costs $2.50 per million input tokens and $5.00 per million output tokens; GPT-5.1-Codex-Max costs $1.25 and $10.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Magnum v4 72B or GPT-5.1-Codex-Max?

GPT-5.1-Codex-Max, with 400K tokens against 33K.

Has any benchmark tested both Magnum v4 72B and GPT-5.1-Codex-Max?

No benchmark has tested both yet. Magnum v4 72B has none yet; GPT-5.1-Codex-Max on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench. Compare them on price and context instead. Data as of October 22, 2026.