ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Ministral 8B Instruct vs Ministral 14B vs Llama-3.1-8B-Instruct

Ministral 14B comes out ahead, 64 to 57 and 56 on our weighted score, though Ministral 8B Instruct is 25% cheaper per token.

  1. Mistral AI

    Ministral 8B Instruct

    Released Oct 16, 2024

    57/100
    • ECI—
    • Price$0.15 / $0.15
    • Context131K
  2. Our pick

    Mistral AI

    Ministral 14B

    Released Dec 2, 2025

    64/100
    • ECI—
    • Price$0.20 / $0.20
    • Context262K
  3. Meta

    Llama-3.1-8B-Instruct

    Released Jul 23, 2024

    56/100
    • ECI116.6
    • Price$0.152 / $0.167
    • Context128K
01 — Verdict

Ministral 14B is our pick

Ministral 14B is the better all-round choice, scoring 64/100 against Ministral 8B Instruct (57) and Llama-3.1-8B-Instruct (56). It leads on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceMinistral 8B InstructMinistral 8B Instruct $0.15 · Llama-3.1-8B-Instruct $0.156 · Ministral 14B $0.20 per 1M tokens (3:1 blend)
  • Longest contextMinistral 14BMinistral 14B 262,144 · Ministral 8B Instruct 131,072 · Llama-3.1-8B-Instruct 128,000 tokens
  • Widest inputsMinistral 14BMinistral 8B Instruct: Text · Ministral 14B: Text, Images · Llama-3.1-8B-Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMinistral 8B InstructMinistral 14BLlama-3.1-8B-Instruct
Price50%898388
Inputs & features30%255025
Context window20%243724
Overall100%57/10064/10056/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Ministral 8B Instruct vs Ministral 14B vs Llama-3.1-8B-Instruct specifications side by side
SpecificationMinistral 8B InstructMistral AIMinistral 14BMistral AILlama-3.1-8B-InstructMeta
Capability
Capabilities Index (ECI)——116.6
ECI rank——#145 of 148
GPQA DiamondGraduate-level science questions27.2% (best)—27.0%
OTIS Mock AIME 2024–2025Competition mathematics——1.7%
Price per million tokens
Input$0.15 (best)$0.20$0.152
Output$0.15 (best)$0.20$0.167
Cached input———
Blended (3:1)$0.15 (best)$0.20$0.156
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 1 providersMedian of 1 providersMedian of 9 providers
Limits
Context window131,072 tokens262,144 tokens (best)128,000 tokens
Max output8,192 tokens262,144 tokens (best)4,096 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenMistral Research LicenseOpenApache-2.0Open
API model ID———
API providers119 (best)
ReleasedOct 16, 2024Dec 2, 2025Jul 23, 2024
Knowledge cutoff——Dec 2023
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Ministral 8B Instruct$1.80
  • Ministral 14B$2.40
  • Llama-3.1-8B-Instruct$1.85
04 — Questions

Which should you choose?

Which is better: Ministral 8B Instruct, Ministral 14B or Llama-3.1-8B-Instruct?

Ministral 14B is the better all-round choice, scoring 64/100 against Ministral 8B Instruct (57) and Llama-3.1-8B-Instruct (56). It leads on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Ministral 8B Instruct, Ministral 14B or Llama-3.1-8B-Instruct?

Ministral 8B Instruct is cheaper at $0.15 input / $0.15 output per million tokens (median across 1 API provider). Llama-3.1-8B-Instruct costs $0.152 input / $0.167 output per million tokens (median across 9 API providers); Ministral 14B costs $0.20 input / $0.20 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Ministral 8B Instruct versus $0.156 for Llama-3.1-8B-Instruct (1× as much) and $0.20 for Ministral 14B (1.3× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Ministral 8B Instruct has not been scored yet, Ministral 14B has not been scored yet and Llama-3.1-8B-Instruct has an ECI of 116.6.

Which is better for coding?

There are no published SWE-bench Verified results for Ministral 8B Instruct, Ministral 14B and Llama-3.1-8B-Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Which has the bigger context window?

Ministral 14B has the largest context window at 262,144 tokens, against 131,072 for Ministral 8B Instruct and 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Ministral 8B Instruct up to 8,192, Ministral 14B up to 262,144, Llama-3.1-8B-Instruct up to 4,096 tokens.

Which can read images, PDFs, audio or video?

Ministral 8B Instruct accepts text; Ministral 14B accepts text and images; Llama-3.1-8B-Instruct accepts text. Ministral 14B handles the widest range of inputs.

Are any of these open source?

Yes, all three publish their weights (Mistral Research License and Apache-2.0), so you can self-host them.

Which is newer?

Ministral 14B is the newest, released Dec 2, 2025. Ministral 8B Instruct came out Oct 16, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Llama-3.1-8B-Instruct Dec 2023.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.