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Comparison · 2 models · Updated Oct 4, 2026

Mistral Large 2.1 vs Llama-3.3-70B-Instruct

Llama-3.3-70B-Instruct comes out ahead, 46 to 38 on our weighted score, and it is the cheaper option too.

  1. Mistral AI

    Mistral Large 2.1

    Released Nov 18, 2024

    38/100
    • ECI128.5
    • Price$2.00 / $6.00
    • Context131K
    Full specs Remove Mistral Large 2.1
  2. Our pick

    Meta

    Llama-3.3-70B-Instruct

    Released Dec 6, 2024

    46/100
    • ECI127.3
    • Price$0.59 / $0.724
    • Context128K
    Full specs Remove Llama-3.3-70B-Instruct

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Llama-3.3-70B-Instruct is our pick

Llama-3.3-70B-Instruct is the better all-round choice, scoring 46/100 against Mistral Large 2.1 (38). It leads on price. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMistral Large 2.1Capabilities Index (ECI): Mistral Large 2.1 128.5 · Llama-3.3-70B-Instruct 127.3
  • Lowest priceLlama-3.3-70B-InstructLlama-3.3-70B-Instruct $0.624 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
  • Longest contextMistral Large 2.1Mistral Large 2.1 131,072 · Llama-3.3-70B-Instruct 128,000 tokens
  • Widest inputsSame inputsMistral Large 2.1: Text · Llama-3.3-70B-Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMistral Large 2.1Llama-3.3-70B-Instruct
CapabilityCapabilities Index (ECI)50%5149
Price25%2760
Inputs & features15%2525
Context window10%2424
Overall100%38/10046/100
02 — Side by side

Every spec in one table

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

Mistral Large 2.1 vs Llama-3.3-70B-Instruct specifications side by side
SpecificationMistral Large 2.1Mistral AILlama-3.3-70B-InstructMeta
Capability
Capabilities Index (ECI)128.5 (best)127.3
ECI rank#130 of 148 (best)#133 of 148
GPQA DiamondGraduate-level science questions51.3% (best)47.4%
OTIS Mock AIME 2024–2025Competition mathematics7.8% (best)5.1%
Price per million tokens
Input$2.00$0.59 (best)
Output$6.00$0.724 (best)
Cached input——
Blended (3:1)$3.00$0.624 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIMedian of 21 providers
Limits
Context window131,072 tokens (best)128,000 tokens
Max output16,384 tokens (best)4,096 tokens
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDmistral-large-2411llama-3.3-70b-instruct
API providers224 (best)
ReleasedNov 18, 2024Dec 6, 2024
Knowledge cutoffNov 2024Dec 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.

  • Mistral Large 2.1$32.00
  • Llama-3.3-70B-Instruct$7.35
04 — Questions

Which should you choose?

Which is better: Mistral Large 2.1 or Llama-3.3-70B-Instruct?

Llama-3.3-70B-Instruct is the better all-round choice, scoring 46/100 against Mistral Large 2.1 (38). It leads on price. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Large 2.1 or Llama-3.3-70B-Instruct?

Llama-3.3-70B-Instruct is cheaper at $0.59 input / $0.724 output per million tokens (median across 21 API providers; free on Llama). Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.624 per million tokens for Llama-3.3-70B-Instruct versus $3.00 for Mistral Large 2.1 (4.8× as much).

Which scores higher on benchmarks?

Mistral Large 2.1 scores higher on the Capabilities Index (ECI): Mistral Large 2.1 128.5 (#130 of 148) and Llama-3.3-70B-Instruct 127.3 (#133 of 148). The confidence ranges of the top two overlap (123.8–130.8 vs 122.5–129.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Llama-3.3-70B-Instruct 47.4%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Llama-3.3-70B-Instruct 5.1%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Large 2.1 and Llama-3.3-70B-Instruct yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2.1 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

Mistral Large 2.1 has the largest context window at 131,072 tokens, against 128,000 for Llama-3.3-70B-Instruct. Maximum output per response: Mistral Large 2.1 up to 16,384, Llama-3.3-70B-Instruct up to 4,096 tokens.

Which can read images, PDFs, audio or video?

Mistral Large 2.1 accepts text; Llama-3.3-70B-Instruct accepts text. They handle the same number of input types.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

Llama-3.3-70B-Instruct is the newest, released Dec 6, 2024. Mistral Large 2.1 came out Nov 18, 2024. Knowledge cutoff: Mistral Large 2.1 Nov 2024, Llama-3.3-70B-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.

05 — Keep comparing

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