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Model A
Grok Code Fast 1

xAI

37.81/100

Supported · Public rank #215

90% interval 34.740.9

Grok Code Fast 1 vs Mistral Large 3

Updated September 3, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Mistral logo
Model B
Mistral Large 3

Mistral

Evidence status unavailable

90% interval unavailable

Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

0 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Chat turn cost

    1K fresh input + 500 output tokens

    Grok Code Fast 1

    Grok Code Fast 1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Grok Code Fast 1

    Grok Code Fast 1 has the lower estimated token cost for this stated workload. Grok Code Fast 1 has no published cached-input rate, so cached tokens use its listed input rate. Mistral Large 3 has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

Show secondary and unsupported calls
  • Repository review cost

    50K fresh input + 3K output tokens

    Grok Code Fast 1

    Grok Code Fast 1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
0
Grok Code Fast 1 only
1
Mistral Large 3 only
0
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Not comparable
Grok Code Fast 1
Not measured
Mistral Large 3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Grok Code Fast 1
70.8
Mistral Large 3
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Grok Code Fast 1
Not measured
Mistral Large 3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Grok Code Fast 1
Not measured
Mistral Large 3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Math

Not comparable
Grok Code Fast 1
Not measured
Mistral Large 3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Grok Code Fast 1
Not measured
Mistral Large 3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Grok Code Fast 1
Not measured
Mistral Large 3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Grok Code Fast 1
Not measured
Mistral Large 3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Grok Code Fast 1
$0.00095
Fits in one request
Mistral Large 3
$0.00125
Fits in one request

Grok Code Fast 1 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Grok Code Fast 1
$0.0145
Fits in one request
Mistral Large 3
$0.0295
Fits in one request

Grok Code Fast 1 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Grok Code Fast 1
$0.059
Fits in one request
Cached input priced at the published list-input rate
Mistral Large 3
$0.125
Fits in one request
Cached input priced at the published list-input rate

Grok Code Fast 1 has the lower modeled cost

Grok Code Fast 1 has no published cached-input rate, so cached tokens use its listed input rate. Mistral Large 3 has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Context window

Maximum documented context; output-token limits may be lower.

Grok Code Fast 1

256K

Mistral Large 3

256K

API model ID

Grok Code Fast 1

Not sourced

Mistral Large 3

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Grok Code Fast 1

Not published

Mistral Large 3

Not published

Documented inputs

Grok Code Fast 1

Not sourced

Mistral Large 3

Not sourced

Documented outputs

Grok Code Fast 1

Not sourced

Mistral Large 3

Not sourced

Provider availability

Grok Code Fast 1

Not sourced

Mistral Large 3

Not sourced

Reasoning profile

Grok Code Fast 1

Non-Reasoning

Mistral Large 3

Non-Reasoning

Weight access

Grok Code Fast 1

Proprietary

Mistral Large 3

Proprietary

License

Grok Code Fast 1

Proprietary

Mistral Large 3

Proprietary

Release date

Grok Code Fast 1

2025-08-28

Mistral Large 3

2025-12-02

If you already use one of these models
Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
Repository review: $0.0145 vs $0.0295. Cache-heavy agent loop: $0.059 vs $0.125.
Context tradeoff
Both models list 256K.

Run the same representative tasks against both endpoints before changing production traffic.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Grok Code Fast 1
API / mo$1,275
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Mistral Large 3
API / mo$1,500
Self-host / mo$9,110
Break-even380M/day
Model the full break-even

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence1 rows

Coding

  • SWE-bench Verified

    Grok Code Fast 170.8%
    Source
    Mistral Large 3

    Not directly comparable

Frequently asked questions

Which is better, Grok Code Fast 1 or Mistral Large 3?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Grok Code Fast 1 or Mistral Large 3?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Grok Code Fast 1 or Mistral Large 3?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Grok Code Fast 1 or Mistral Large 3?

For the stated presets, chat costs $0.00095 on Grok Code Fast 1 and $0.00125 on Mistral Large 3; repository review costs $0.0145 and $0.0295; the cache-heavy agent loop costs $0.059 and $0.125. Grok Code Fast 1 has no published cached-input rate, so cached tokens use its listed input rate. Mistral Large 3 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Grok Code Fast 1 or Mistral Large 3?

Both models list the same context window, 256K.

Related comparisons

Last updated September 3, 2026

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